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Posts from the ‘Zero Trust Privilege’ Category

Top 10 Cybersecurity Companies To Watch In 2019

Today’s Threatscape Has Made “Trust But Verify” Obsolete 

The threatscape every business operates in today is proving the old model of “trust but verify” obsolete and in need of a complete overhaul. To compete and grow in the increasingly complex and lethal threatscape of today, businesses need more adaptive, contextually intelligent security solutions based on the Zero Trust Security framework. Zero Trust takes a “never trust, always verify, enforce least privilege” approach to privileged access, from inside or outside the network. John Kindervag was the first to see how urgent the need was for enterprises to change their approach to cybersecurity, so he created the Zero Trust Security framework in 2010 while at Forrester. Chase Cunningham, Principal Analyst at Forrester, is a mentor to many worldwide wanting to expand their knowledge of Zero Trust and frequently speaks and writes on the topic. If you are interested in cybersecurity in general and Zero Trust specifically, be sure to follow his blog.

AI and machine learning applied to cybersecurity’s most significant challenges is creating a proliferation of commercially successful, innovative platforms. The size and scale of deals in cybersecurity continue to accelerate with BlackBerry’s acquisition of Cylance for $1.4B in cash closing in February of this year being the largest. TD Ameritrade’s annual survey of registered investment advisors (RIA) showed nearly a 6X jump in cybersecurity investments this year compared to 2018.

The top ten cybersecurity companies reflect the speed and scale of innovation happening today that are driving the highest levels of investment this industry has ever seen. The following are the top ten cybersecurity companies to watch in 2019:

Absolute (ABT.TO)  – One of the world’s leading commercial enterprise security solutions, serving as the industry benchmark for endpoint resilience, visibility, and control. The company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications whether endpoints are on or off the network, and the ultimate level of control and confidence required for the modern enterprise. Embedded in over one billion endpoint devices, Absolute delivers intelligence and real-time remediation capabilities that equip enterprises to stop data breaches at the source.

To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $124B will be spent on security in 2019 aloneAbsolute’s 2019 Endpoint Security Trends Report finds that much of that spend is in vain, however, revealing that 70% of all breaches still originate on the endpoint. The problem is complexity at the endpoint – it causes security agents to fail invariably, reliably, and predictably.

Absolute’s research found that 42% of all endpoints are unprotected at any given time, and 100% of endpoint security tools eventually fail. As a result, IT leaders see a negative ROI on their security spend. What makes Absolute one of the top 10 security companies to watch in 2019 is their purpose-driven design to mitigate this universal law of security decay.

Enterprises rely on Absolute to cut through the complexity to identify failures, model control options, and refocus security intent. Rather than perpetuating organizations’ false sense of security, Absolute enables uncompromised endpoint persistence, builds resilience and delivers the intelligence needed to ensure security agents, applications, and controls continue functioning and deliver value as intended. Absolute has proven very effective in validating safeguards, fortifying endpoints, and stopping data security compliance failures. The following is an example of the Absolute platform at work:

BlackBerry Artifical Intelligence and Predictive Security  –  BlackBerry is noteworthy for how quickly they are reinventing themselves into an enterprise-ready cybersecurity company independent of the Cylance acquisition. Paying $1.4B in cash for Cylance brings much-needed AI and machine learning expertise to their platform portfolio, an acquisition that BlackBerry is moving quickly to integrate into their product and service strategies. BlackBerry Cylance uses AI and machine learning to protect the entire attack surface of an enterprise with automated threat prevention, detection, and response capabilities. Cylance is also the first company to apply artificial intelligence, algorithmic science, and machine learning to cyber security and improve the way companies, governments, and end users proactively solve the world’s most challenging security problems. Using a breakthrough mathematical process, BlackBerry Cylance quickly and accurately identifies what is safe and what is a threat, not just what is in a blacklist or whitelist. By coupling sophisticated math and machine learning with a unique understanding of a hacker’s mentality, BlackBerry Cylance provides the technology and services to be truly predictive and preventive against advanced threats. The following screen from CylancePROTECT provides an executive summary of CylancePROTECT usage, from the number of zones and devices to the percentage of devices covered by Auto-Quarantine and Memory Protection, Threat Events, Memory Violations, Agent Versions, and Offline Days for devices.

Centrify –  Centrify is redefining the legacy approach to Privileged Access Management by delivering cloud-ready Zero Trust Privilege to secure modern enterprise attack surfaces. Centrify Zero Trust Privilege helps customers grant least privilege access based on verifying who is requesting access, the context of the request, and the risk of the access environment. Industry research firm Gartner predicted Privileged Access Management (PAM) to be the second-fastest growing segment for information security and risk management spending worldwide in 2019 in their recent Forecast Analysis: Information Security and Risk Management, Worldwide, 3Q18 Update (client access required). By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse. PAM was also named a Top 10 security project for 2019 in Gartner’s Top 10 Security Projects for 2019 (client access required).
CloudFlare –  Cloudflare is a web performance and security company that provides online services to protect and accelerate websites online. Its online platforms include Cloudflare CDN that distributes content around the world to speed up websites, Cloudflare Optimizer that enables web pages with ad servers and third-party widgets to download Snappy software on mobiles and computers, CloudFlare Security that protects websites from a range of online threats including spam, SQL injection, and DDOS, Cloudflare Analytics that gives insight into website’s traffic including threats and search engine crawlers, Keyless SSL that allows organizations to keep secure sockets layer (SSL) keys private, and Cloudflare applications that help its users install web applications on their websites.

CrowdStrike – Applying machine learning to endpoint detection of IT network threats is how CrowdStrike is differentiating itself in the rapidly growing cybersecurity market today. It’s also one of the top 25 machine learning startups to watch in 2019. Crowdstrike is credited with uncovering Russian hackers inside the servers of the US Democratic National Committee. The company’s IPO was last Tuesday night, with an initial $34/per share price. Their IPO generated $610M at a valuation at one point reaching nearly $7B. Their Falcon platform stops breaches by detecting all attacks types, even malware-free intrusions, providing five-second visibility across all current and past endpoint activity while reducing cost and complexity for customers. CrowdStrike’s Threat Graph provides real-time analysis of data from endpoint events across the global crowdsourcing community, allowing detection and prevention of attacks based on patented behavioral pattern recognition technology.

Hunters.AI – Hunters.AI excels at autonomous threat hunting by capitalizing on its autonomous system that connects to multiple channels within an organization and detects the signs of potential cyber-attacks. They are one of the top 25 machine learning startups to watch in 2019. What makes this startup one of the top ten cybersecurity companies to watch in 2019 is their innovative approach to creating AI- and machine learning-based algorithms that continually learn from an enterprise’s existing security data. Hunters.AI generates and delivers visualized attack stories allowing organizations to more quickly and effectively identify, understand, and respond to attacks. Early customers, including Snowflake Computing, whose VP of Security recently said, “Hunters.AI identified the attack in minutes. In my 20 years in security, I have not seen anything as effective, fast, and with high fidelity as what Hunters can do.”  The following is a graphic overview of how their system works:

Idaptive – Idaptive is noteworthy for the Zero Trust approach they are taking to protecting organizations across every threat surface they rely on operate their businesses dally. Idaptive secures access to applications and endpoints by verifying every user, validating their devices, and intelligently limiting their access. Their product and services strategy reflects a “never trust, always verify, enforce least privilege” approach to privileged access, from inside or outside the network. The Idaptive Next-Gen Access platform combines single single-on (SSO), adaptive multifactor authentication (MFA), enterprise mobility management (EMM) and user behavior analytics (UBA). They have over 2,000 organizations using their platform today. Idaptive was spun out from Centrify on January 1st of this year.

Kount – Kount has successfully differentiated itself in an increasingly crowded cybersecurity marketplace by providing fraud management, identity verification and online authentication technologies that enable digital businesses, online merchants and payment service providers to identify and thwart a wide spectrum of threats in real-time. Kount has been able to show through customer references that their customers can approve more orders, uncover new revenue streams, and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with policy and rules management, their customers thwart online criminals and bad actors driving them away from their site, their marketplace and off their network. Kount’s continuously adaptive platform learns of new threats and continuously updates risk scores to further thwart breach and fraud attempts. Kount’s advances in both proprietary techniques and patented technology include: Superior mobile fraud detection, Advanced artificial intelligence, Multi-layer device fingerprinting, IP proxy detection and geo-location, Transaction and custom scoring, Global order linking, Business intelligence reporting, Comprehensive order management, Professional and managed services. Kount protects over 6,500 brands today.

MobileIron –  The acknowledged leader in Mobile Device Management software, MobileIron’s latest series of developments make them noteworthy and one of the top ten cybersecurity companies to watch in 2019.   MobileIron was the first to deliver key innovations such as multi-OS mobile device management (MDM), mobile application management (MAM), and BYOD privacy controls. Last month MobileIron introduced zero sign-on (ZSO), built on the company’s unified endpoint management (UEM) platform and powered by the MobileIron Access solution. “By making mobile devices your identity, we create a world free from the constant pains of password recovery and the threat of data breaches due to easily compromised credentials,” wrote Simon Biddiscombe, MobileIron’s President and Chief Executive Officer in his recent blog post, Single sign-on is still one sign-on too many. Simon’s latest post, MobileIron: We’re making history by making passwords history, provides the company’s vision going forward with ZSO. Zero sign-on eliminates passwords as the primary method for user authentication, unlike single sign-on, which still requires at least one username and password. MobileIron paved the way for a zero sign-on enterprise with its Access product in 2017, which enabled zero sign-on to cloud services on managed devices. Enterprise security teams no longer have to trade off security for better user experience, thanks to the MobileIron Zero Sign-On.

Sumo Logic – Sumo Logic is a fascinating cybersecurity company to track because it shows the ability to take on large-scale enterprise security challenges and turn them into a competitive advantage. An example of this is how quickly the company achieved FedRAMP Ready Designation, getting listed in the FedRAMP Marketplace. Sumo Logic is a secure, cloud-native, machine data analytics service, delivering real-time, continuous intelligence from structured, semi-structured, and unstructured data across the entire application lifecycle and stack. More than 2,000 customers around the globe rely on Sumo Logic for the analytics and insights to build, run, and secure their modern applications and cloud infrastructures. With Sumo Logic, customers gain a multi-tenant, service-model advantage to accelerate their shift to continuous innovation, increasing competitive advantage, business value, and growth. Founded in 2010, Sumo Logic is a privately held company based in Redwood City, Calif. and is backed by Accel Partners, Battery Ventures, DFJ, Franklin Templeton, Greylock Partners, IVP, Sapphire Ventures, Sequoia Capital, Sutter Hill Ventures and Tiger Global Management.

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Machine Learning Is Helping To Stop Security Breaches With Threat Analytics

Bottom Line: Machine learning is enabling threat analytics to deliver greater precision regarding the risk context of privileged users’ behavior, creating notifications of risky activity in real time, while also being able to actively respond to incidents by cutting off sessions, adding additional monitoring, or flagging for forensic follow-up.

Separating Security Hacks Fact from Fiction

It’s time to demystify the scale and severity of breaches happening globally today. A commonly-held misconception or fiction is that millions of hackers have gone to the dark side and are orchestrating massive attacks on any and every business that is vulnerable. The facts are far different and reflect a much more brutal truth, which is that businesses make themselves easy to hack into by not protecting their privileged access credentials. Cybercriminals aren’t expending the time and effort to hack into systems; they’re looking for ingenious ways to steal privileged access credentials and walk in the front door. According to Verizon’s 2019 Data Breach Investigations Report, ‘Phishing’ (as a pre-cursor to credential misuse), ‘Stolen Credentials’, and ‘Privilege Abuse’ account for the majority of threat actions in breaches (see page 9 of the report).

It only really takes one compromised credential to potentially impact millions — whether it’s millions of individuals or millions of dollars. Undeniably, identities and the trust we place in them are being used against us. They have become the Achilles heel of our cybersecurity practices. According to a recent study by Centrify among 1,000 IT decision makers, 74% of respondents whose organizations have been breached acknowledged that it involved access to a privileged account. This number closely aligns with Forrester Research’s estimate “that at least 80% of data breaches . . . [involved] compromised privileged credentials, such as passwords, tokens, keys, and certificates.”

While the threat actors might vary according to Verizon’s 2019 Data Breach Investigations Report, the cyber adversaries’ tactics, techniques, and procedures are the same across the board. Verizon found that the fastest growing source of threats are from internal actors, as the graphic from the study illustrates below:


Internal actors are the fastest growing source of breaches because they’re able to obtain privileged access credentials with minimal effort, often obtaining them through legitimate access requests to internal systems or harvesting their co-workers’ credentials by going through the sticky notes in their cubicles. Privileged credential abuse is a challenge to detect as legacy approaches to cybersecurity trust the identity of the person using the privileged credentials. In effect, the hacker is camouflaged by the trust assigned to the privileged credentials they have and can roam internal systems undetected, exfiltrating sensitive data in the process.

The reality is that many breaches can be prevented by some of the most basic Privileged Access Management (PAM) tactics and solutions, coupled with a Zero Trust approach. Most organizations are investing the largest chunk of their security budget on protecting their network perimeter rather than focusing on security controls, which can affect positive change to protect against the leading attack vector: privileged access abuse.

The bottom line is that investing in securing perimeters leaves the most popular attack vector of all unprotected, which are privileged credentials. Making PAM a top priority is crucial to protect any business’ most valuable asset; it’s systems, data, and the intelligence they provide. Gartner has listed PAM on its Top 10 Security Projects for the past two years for a good reason.

Part of a cohesive PAM strategy should include machine learning-based threat analytics to provide an extra layer of security that goes beyond a password vault, multi-factor authentication (MFA), or privilege elevation.

How Machine Learning and Threat Analytics Stop Privileged Credential Abuse 

Machine learning algorithms enable threat analytics to immediately detect anomalies and non-normal behavior by tracking login behavioral patterns, geolocation, and time of login, and many more variables to calculate a risk score. Risk scores are calculated in real-time and define if access is approved, if additional authentication is needed, or if the request is blocked entirely.

Machine learning-based threat analytics also provide the following benefits:

  • New insights into privileged user access activity based on real-time data related to unusual recent privilege change, the command runs, target accessed, and privilege elevation.
  • Gain greater understanding and insights into the specific risk nature of specific events, computing a risk score in real time for every event expressed as high, medium, or low level for any anomalous activity.
  •  Isolate, identify, and track which security factors triggered an anomaly alert.
  • Capture, play, and analyze video sessions of anomalous events within the same dashboard used for tracking overall security activity.
  • Create customizable alerts that provide context-relevant visibility and session recording and can also deliver notifications of anomalies, all leading to quicker, more informed investigative action.

What to Look for In Threat Analytics 
Threat analytics providers are capitalizing on machine learning to improve the predictive accuracy and usability of their applications continually. What’s most important is for any threat analytics application or solution you’re considering to provide context-aware access decisions in real time. The best threat analytics applications on the market today are using machine learning as the foundation of their threat analytics engine. These machine learning-based engines are very effective at profiling the normal behavior pattern for any user on any login attempt, or any privileged activity including commands, identifying anomalies in real time to enable risk-based access control. High-risk events are immediately flagged, alerted, notified, and elevated to IT’s attention, speeding analysis, and greatly minimizing the effort required to assess risk across today’s hybrid IT environments.

The following is the minimum set of features to look for in any privilege threat analytics solution:

  • Immediate visibility with a flexible, holistic view of access activity across an enterprise-wide IT network and extended partner ecosystem. Look for threat analytics applications that provide dashboards and interactive widgets to better understand the context of IT risk and access patterns across your IT infrastructure. Threat analytics applications that give you the flexibility of tailoring security policies to every user’s behavior and automatically flagging risky actions or access attempts, so that you’ll gain immediate visibility into account risk, eliminating the overhead of sifting through millions of log files and massive amounts of historical data.
  • They have intuitively designed and customizable threat monitoring and investigation screens, workflows, and modules. Machine learning is enabling threat analytics applications to deliver more contextually-relevant and data-rich insights than has ever been possible in the past. Look for threat analytics vendors who offer intuitively designed and customizable threat monitoring features that provide insights into anomalous activity with a detailed timeline view. The best threat analytics vendors can identify the specific factors contributing to an anomaly for a comprehensive understanding of a potential threat, all from a single console. Security teams can then view system access, anomaly detection in high resolutions with analytics tools such as dashboards, explorer views, and investigation tools.
  • Must provide support for easy integration to Security Information and Event Management (SIEM) tools. Privileged access data is captured and stored to enable querying by log management and SIEM reporting tools. Make sure any threat analytics application you’re considering has installed, and working integrations with SIEM tools and platforms such as Micro Focus® ArcSight™, IBM® QRadar™, and Splunk® to identify risks or suspicious activity quickly.
  • Must Support Alert Notification by Integration with Webhook-Enabled Endpoints. Businesses getting the most value out of their threat analytics applications are integrating with Slack or existing onboard incident response systems such as PagerDuty to enable real-time alert delivery, eliminating the need for multiple alert touch points and improving time to respond. When an alert event occurs, the threat analytics engine allows the user to send alerts into third-party applications via Webhook. This capability enables the user to respond to a threat alert and contain the impact of a breach attempt.

Conclusion 
CentrifyForresterGartner, and Verizon each have used different methodologies and reached the same conclusion from their research: privileged access abuse is the most commonly used tactic for hackers to exfiltrate sensitive data. Breaches based on privileged credential abuse are extremely difficult to stop, as these credentials often have the greatest levels of trust and access rights associated with them. Leveraging threat analytics applications using machine learning that is adept at finding anomalies in behavioral data and thwarting a breach by denying access is proving very effective against privileged credential abuse.

Companies, including Centrify, use risk scoring combined with adaptive MFA to empower a least-privilege access approach based on Zero Trust. This Zero Trust Privilege approach verifies who or what is requesting privileged access, the context behind the request, and the risk of the access environment to enforce least privilege. These are the foundations of Zero Trust Privilege and are reflected in how threat analytics apps are being created and improved today.

How The Top 21% Of PAM-Mature Enterprises Are Thwarting Privileged Credential Breaches

  • Energy, Technology & Finance are the most mature industries when it comes to Privileged Access Management (PAM) adoption and uses, outscoring peer industries by a wide margin.
  • 58% of organizations do not use Multi-Factor Authentication (MFA) for privileged administrative access to servers, leaving their IT systems and infrastructure exposed to hacking attempts, including unchallenged privileged access abuse.
  • 52% of organizations are using shared accounts for controlling privileged access, increasing the probability of privileged credential abuse.

These and many other fascinating insights are from the recently published Centrify 2019 Zero Trust Privilege Maturity Model Report created in partnership with Techvangelism. You can download a copy of the study here (PDF, 22 pp., no opt-in). Over 1,300 organizations participated in the survey from 11 industries with Technology, Finance, and Healthcare, comprising 50% of all organizations participating. Please see page 4 of the study for additional details regarding the methodology.

What makes this study noteworthy is that it’s the first of its kind to create a Zero Trust Privilege Maturity Model designed to help organizations better understand and define their ability to discover, protect, secure, manage, and provide privileged access. Also, this model can be used to help mature existing security implementations towards one that provides the greatest level of protection of identity, privileged access, and its use.

Key takeaways from the study include the following:

  • The top 21% of enterprises who excel at thwarting privileged credential breaches share a common set of attributes that differentiate them from their peers. Enterprises who most succeed at stopping security breaches have progressed beyond vault- and identity-centric techniques by hardening their environments through the use of centralized management of service and application accounts and enforcing host-based session, file, and process auditing. In short, the most secure organizations globally have reached a level of Privileged Access Management (PAM) maturity that reduces the probability of a breach successfully occurring due to privileged credential abuse.

  • Energy, Technology & Finance are the most mature industries adopting Privileged Access Management (PAM), outscoring peer industries by a wide margin. Government, Education, and Manufacturing are the industries most lagging in their adoption of Zero Trust Privilege (ZTP), making them the most vulnerable to breaches caused by privileged credential abuse. Education and Manufacturing are the most vulnerable industries of all, where it’s common for multiple manufacturing sites to use shared accounts for controlling privileged access. The study found shared accounts for controlling privileged access is commonplace, with 52% of all organizations reporting this occurring often. Presented below are the relative levels of Zero Trust Privilege Maturity by demographics, with the largest organizations having the most mature approaches to ZTP, which is expected given the size and scale of their IT and cybersecurity departments.

  • 51% of organizations do not control access to transformational technologies with privileged access, including modern attack surfaces such as cloud workloads (38%), Big Data projects (65%), and containers (50%). Artificial Intelligence (AI)/Bots and Internet of Things (IoT) are two of the most vulnerable threat surfaces according to the 1,300 organizations surveyed. Just 16% of organizations have implemented a ZTP strategy to protect their AI/Bots technologies, and just 25% have implemented them for IoT. The graphic below compares usage or plans by transformational technologies.

  • 58% of organizations aren’t using MFA for server login, and 25% have no plans for a password vault, two areas that are the first steps to defining a Privileged Access Management (PAM) strategy. Surprisingly, 26% do not use and do not plan to use MFA for server login, while approximately 32% do plan to use MFA for server logins. Organizations are missing out on opportunities to significantly harden their security posture by adopting password vaults and implementing MFA across all server logins. These two areas are essential for implementing a ZTP framework.

Conclusion

To minimize threats – both external and internal – Privileged Access Management needs to go beyond the fundamental gateway-based model and look to encompass host-enforced privileged access that addresses every means by which the organization leverages privileged credentials. With just 21% of organizations succeeding with mature Zero Trust Privilege deployments, 79% are vulnerable to privileged credential abuse-based breaches that are challenging to stop. Privileged credentials are the most trusted in an organization, allowing internal and external hackers the freedom to move throughout networks undetected. That’s why understanding where an organization is on the spectrum of ZTP maturity is so important, and why the findings from the Centrify and Techvangelism 2019 Zero Trust Privilege Maturity Model Report are worth noting and taking action on.

How To Improve Privileged User’s Security Experiences With Machine Learning

Bottom Line: One of the primary factors motivating employees to sacrifice security for speed are the many frustrations they face, attempting to re-authenticate who they are so they can get more work done and achieve greater productivity.

How Bad Security Experiences Lead to a Breach

Every business is facing the paradox of hardening security without sacrificing users’ login and system access experiences. Zero Trust Privilege is emerging as a proven framework for thwarting privileged credential abuse by verifying who is requesting access, the context of the request, and the risk of the access environment across every threat surface an organization has.

Centrify’s recent survey Privileged Access Management In The Modern Threatscape found that 74% of data breaches start with privileged credential abuse. Forrester estimates that 80% of data breaches have a connection to compromised privileged credentials, such as passwords, tokens, keys, and certificates. On the Dark Web, privileged access credentials are a best-seller because they provide the intruder with “the keys to the kingdom.” By leveraging a “trusted” identity, a hacker can operate undetected and exfiltrate sensitive data sets without raising any red flags.

Frustrated with wasting time responding to the many account lock-outs, re-authentication procedures, and login errors outmoded Privileged Access Management (PAM) systems require, IT Help Desk teams, IT administrators, and admin users freely share privileged credentials, often resulting in them eventually being offered for sale on the Dark Web.

The Keys to the Kingdom Are In High Demand

18% of healthcare employees are willing to sell confidential data to unauthorized parties for as little as $500 to $1,000, and 24% of employees know of someone who has sold privileged credentials to outsiders, according to a recent Accenture survey. State-sponsored and organized crime organizations offer to pay bounties in bitcoin for privileged credentials for many of the world’s largest financial institutions on the Dark Web. And with the typical U.S.-based enterprise losing on average $7.91M from a breach, more than double the global average of $3.86M according to IBM’s 2018 Data Breach Study, it’s clear that improving admin user experiences to reduce the incidence of privileged credential sharing needs to happen now.

How Machine Learning Improves Admin User Experiences and Thwarts Breaches

Machine learning is making every aspect of security experiences more adaptive, taking into account the risk context of every privileged access attempt across any threat surface, anytime. Machine learning algorithms can continuously learn and generate contextual intelligence that is used to streamline verified privileged user’s access while thwarting many potential threats ― the most common of which is compromised credentials.

The following are a few of the many ways machine learning is improving privileged users’ experiences when they need to log in to secure critical infrastructure resources:

  • Machine learning is making it possible to provide adaptive, personalized login experiences at scale using risk-scoring of every access attempt in real-time, all contributing to improved user experiences. Machine learning is making it possible to implement security strategies that flex or adapt to risk contexts in real-time, assessing every access attempt across every threat surface, and generating a risk score in milliseconds. Being able to respond in milliseconds, or real-time is essential for delivering excellent admin user experiences. The “never trust, always verify, enforce least privilege” approach to security is how many enterprises from a broad base of industries including leading financial services and insurance companies are protecting every threat surface from privileged access abuse. CIOs at these companies say taking a Zero Trust approach with a strong focus on Zero Trust Privilege corporate-wide is redefining the legacy approach to Privileged Access Management by delivering cloud-architected Zero Trust Privilege to secure access to infrastructure, DevOps, cloud, containers, Big Data, and other modern enterprise use cases. Taking a Zero Trust approach to security enables their departments to roll out new services across every threat surface their customers prefer to use without having to customize security strategies for each.
  • Quantify, track and analyze every potential security threat and attempted breach and apply threat analytics to the aggregated data sets in real-time, thwarting data exfiltration attempts before they begin. One of the tenets or cornerstones of Zero Trust Privilege is adaptive control. Machine learning algorithms continually “learn” by continuously analyzing and looking for anomalies in users’ behavior across every threat surface, device, and login attempt. When any users’ behavior appears to be outside the threshold of constraints defined for threat analytics and risk scoring, additional authentication is immediately requested, and access denied to requested resources until an identity can be verified. Machine learning makes adaptive preventative controls possible.
  • When every identity is a new security perimeter, machine learnings’ ability to provide personalization at scale for every access attempt on every threat surface is essential for enabling a company to keep growing. Businesses that are growing the fastest often face the greatest challenges when it comes to improving their privileged users’ experiences. Getting new employees productive quickly needs to be based on four foundational elements. These include verifying the identity of every admin user, knowing the context of their access request, ensuring it’s coming from a clean source, and limiting access as well as privilege. Taken together, these pillars form the foundation of a Zero Trust Privilege.

Conclusion

Organizations don’t have to sacrifice security for speed when they’re relying on machine learning-based approaches for improving the privileged user experience. Today, a majority of IT Help Desk teams, IT administrators, and admin users are freely sharing privileged credentials to be more productive, which often leads to breaches based on privileged access abuse. By taking a machine learning-based approach to validate every access request, the context of the request, and the risk of the access environment, roadblocks in the way of greater privileged user productivity disappear. Privileged credential abuse is greatly minimized.

How To Improve Supply Chains With Machine Learning: 10 Proven Ways

Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionizing supply chain management in the process.

Machine learning algorithms and the models they’re based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. From Amazon’s Kiva robotics relying on machine learning to improve accuracy, speed and scale to DHL relying on AI and machine learning to power their Predictive Network Management system that analyzes 58 different parameters of internal data to identify the top factors influencing shipment delays, machine learning is defining the next generation of supply chain management. Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions. Gartner is also predicting by 2023 intelligent algorithms, and AI techniques will be an embedded or augmented component across 25% of all supply chain technology solutions.

The ten ways that machine learning is revolutionizing supply chain management include:

  • Machine learning-based algorithms are the foundation of the next generation of logistics technologies, with the most significant gains being made with advanced resource scheduling systems. Machine learning and AI-based techniques are the foundation of a broad spectrum of next-generation logistics and supply chain technologies now under development. The most significant gains are being made where machine learning can contribute to solving complex constraint, cost and delivery problems companies face today. McKinsey predicts machine learning’s most significant contributions will be in providing supply chain operators with more significant insights into how supply chain performance can be improved, anticipating anomalies in logistics costs and performance before they occur. Machine learning is also providing insights into where automation can deliver the most significant scale advantages. Source: McKinsey & Company, Automation in logistics: Big opportunity, bigger uncertainty, April 2019. By Ashutosh Dekhne, Greg Hastings, John Murnane, and Florian Neuhaus

  • The wide variation in data sets generated from the Internet of Things (IoT) sensors, telematics, intelligent transport systems, and traffic data have the potential to deliver the most value to improving supply chains by using machine learning. Applying machine learning algorithms and techniques to improve supply chains starts with data sets that have the greatest variety and variability in them. The most challenging issues supply chains face are often found in optimizing logistics, so materials needed to complete a production run arrive on time. Source: KPMG, Supply Chain Big Data Series Part 1

  • Machine learning shows the potential to reduce logistics costs by finding patterns in track-and-trace data captured using IoT-enabled sensors, contributing to $6M in annual savings. BCG recently looked at how a decentralized supply chain using track-and-trace applications could improve performance and reduce costs. They found that in a 30-node configuration when blockchain is used to share data in real-time across a supplier network, combined with better analytics insight, cost savings of $6M a year is achievable. Source: Boston Consulting Group, Pairing Blockchain with IoT to Cut Supply Chain Costs, December 18, 2018, by Zia Yusuf, Akash Bhatia, Usama Gill, Maciej Kranz, Michelle Fleury, and Anoop Nannra

  • Reducing forecast errors up to 50% is achievable using machine learning-based techniques. Lost sales due to products not being available are being reduced up to 65% through the use of machine learning-based planning and optimization techniques. Inventory reductions of 20 to 50% are also being achieved today when machine learning-based supply chain management systems are used. Source: Digital/McKinsey, Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (PDF, 52 pp., no opt-in).

  • DHL Research is finding that machine learning enables logistics and supply chain operations to optimize capacity utilization, improve customer experience, reduce risk, and create new business models. DHL’s research team continually tracks and evaluates the impact of emerging technologies on logistics and supply chain performance. They’re also predicting that AI will enable back-office automation, predictive operations, intelligent logistics assets, and new customer experience models. Source: DHL Trend Research, Logistics Trend Radar, Version 2018/2019 (PDF, 55 pp., no opt-in)

  • Detecting and acting on inconsistent supplier quality levels and deliveries using machine learning-based applications is an area manufacturers are investing in today. Based on conversations with North American-based mid-tier manufacturers, the second most significant growth barrier they’re facing today is suppliers’ lack of consistent quality and delivery performance. The greatest growth barrier is the lack of skilled labor available. Using machine learning and advanced analytics manufacturers can discover quickly who their best and worst suppliers are, and which production centers are most accurate in catching errors. Manufacturers are using dashboards much like the one below for applying machine learning to supplier quality, delivery and consistency challenges. Source: Microsoft, Supplier Quality Analysis sample for Power BI: Take a tour, 2018

  • Reducing risk and the potential for fraud, while improving the product and process quality based on insights gained from machine learning is forcing inspection’s inflection point across supply chains today. When inspections are automated using mobile technologies and results are uploaded in real-time to a secure cloud-based platform, machine learning algorithms can deliver insights that immediately reduce risks and the potential for fraud. Inspectorio is a machine learning startup to watch in this area. They’re tackling the many problems that a lack of inspection and supply chain visibility creates, focusing on how they can solve them immediately for brands and retailers. The graphic below explains their platform. Source: Forbes, How Machine Learning Improves Manufacturing Inspections, Product Quality & Supply Chain Visibility, January 23, 2019

  • Machine learning is making rapid gains in end-to-end supply chain visibility possible, providing predictive and prescriptive insights that are helping companies react faster than before. Combining multi-enterprise commerce networks for global trade and supply chain management with AI and machine learning platforms are revolutionizing supply chain end-to-end visibility. One of the early leaders in this area is Infor’s Control Center. Control Center combines data from the Infor GT Nexus Commerce Network, acquired by the company in September 2015, with Infor’s Coleman Artificial Intelligence (AI) Infor chose to name their AI platform after the inspiring physicist and mathematician Katherine Coleman Johnson, whose trail-blazing work helped NASA land on the moon. Be sure to pick up a copy of the book and see the movie Hidden Figures if you haven’t already to appreciate her and many other brilliant women mathematicians’ many contributions to space exploration. ChainLink Research provides an overview of Control Center in their article, How Infor is Helping to Realize Human Potential, and two screens from Control Center are shown below.

  • Machine learning is proving to be foundational for thwarting privileged credential abuse which is the leading cause of security breaches across global supply chains. By taking a least privilege access approach, organizations can minimize attack surfaces, improve audit and compliance visibility, and reduce risk, complexity, and the costs of operating a modern, hybrid enterprise. CIOs are solving the paradox of privileged credential abuse in their supply chains by knowing that even if a privileged user has entered the right credentials but the request comes in with risky context, then stronger verification is needed to permit access.  Zero Trust Privilege is emerging as a proven framework for thwarting privileged credential abuse by verifying who is requesting access, the context of the request, and the risk of the access environment.  Centrify is a leader in this area, with globally-recognized suppliers including Cisco, Intel, Microsoft, and Salesforce being current customers.  Source: Forbes, High-Tech’s Greatest Challenge Will Be Securing Supply Chains In 2019, November 28, 2018.
  • Capitalizing on machine learning to predict preventative maintenance for freight and logistics machinery based on IoT data is improving asset utilization and reducing operating costs. McKinsey found that predictive maintenance enhanced by machine learning allows for better prediction and avoidance of machine failure by combining data from the advanced Internet of Things (IoT) sensors and maintenance logs as well as external sources. Asset productivity increases of up to 20% are possible and overall maintenance costs may be reduced by up to 10%. Source: Digital/McKinsey, Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? (PDF, 52 pp., no opt-in).

References

Accenture, Reinventing The Supply Chain With AI, 20 pp., PDF, no opt-in.

Bendoly, E. (2016). Fit, Bias, and Enacted Sensemaking in Data Visualization: Frameworks for Continuous Development in Operations and Supply Chain Management Analytics. Journal Of Business Logistics37(1), 6-17.

Boston Consulting Group, Pairing Blockchain with IoT to Cut Supply Chain Costs, December 18, 2018, by Zia Yusuf, Akash Bhatia, Usama Gill, Maciej Kranz, Michelle Fleury, and Anoop Nannra

How To Secure Mobile Devices In A Zero Trust World

  • 86% of enterprises are seeing mobile threats growing the fastest this year, outpacing other threat types.
  • 48% say they’ve sacrificed security to “get the job done” up from 32% last year.
  • 41% of those affected say the compromise is having major with lasting repercussions and 43% said that their efforts to remediate the attacks were “difficult and expensive.”

Bottom Line: The majority of enterprises, 67%, are the least confident in the security of their mobile assets than any other device or platform today according to Verizon’s Mobile Security Index 2019.

Why Mobile Devices Are the Fastest Growing Threat Surface Today     

Verizon found that 86% of enterprises see an upswing in the number, scale, and scope of mobile breach attempts in 2019. When broken out by industry, Financial Services, Professional Services, and Education are the most commonly targeted industries as the graphic below shows:

The threat surfaces every organization needs to protect is exponentially increasing today based on the combination of employee- and company-owned mobile devices. 41% of enterprises rate mobile devices as their most vulnerable threat surface this year:

Passwords and Mobile Devices Have Become A Hacker’s Paradise

“The only people who love usernames and passwords are hackers,” said Alex Simons, corporate vice president at Microsoft’s identity division in a recent Wall Street Journal article, Username and Password Hell: Why the Internet Can’t Keep You Logged In. Verizon found that mobile devices are the most vulnerable, fastest-growing threat surface there is, making it a favorite with state-sponsored and organized crime syndicates. How rapidly mobile devices are proliferating in enterprises today frequently outpace their ability to secure them, falling back on legacy Privileged Access Management (PAM) approaches that hacking syndicates know how to get around easily using compromised passwords and privileged access credentials. Here’s proof of how much of a lucrative paradise it is for hackers to target passwords and mobile devices first:

  • Hacker’s favorite way to gain access to any business is by using privileged access credentials, which are increasingly being harvested from cellphones using malware. Hacking organizations would rather walk in the front door of any organizations’ systems rather than expend the time and effort to hack in. It’s by far the most popular approach with hackers, with 74% of IT decision makers whose organizations have been breached in the past say it involved privileged access credential abuse according to a recent Centrify survey, Privileged Access Management in the Modern Threatscape. Only 48% of the organizations have a password vault, and just 21% have multi-factor authentication (MFA) implemented for privileged administrative access. The Verizon study found that malware is the most common strategy hackers use to gain access to corporate networks. MobileIron’s Global Threat Report, mid-year 2018 found that 3.5% of Android devices are harboring known malware. Of these malicious apps, over 80% had access to internal networks and were scanning nearby ports. This suggests that the malware was part of a larger attack.

Securing Mobile Devices In A Zero Trust World Needs To Happen Now

Mobile devices are an integral part of everyone’s identity today. They are also the fastest growing threat surface for every business – making identities the new security perimeter. Passwords are proving to be problematic in scaling fast enough to protect these threat surfaces, as credential abuse is skyrocketing today. They’re perennial best-sellers on the Dark Web, where buyers and sellers negotiate in bitcoin for companies’ logins and passwords – often with specific financial firms, called out by name in “credentials wanted” ads. Organizations are waking up to the value of taking a Zero Trust approach to securing their businesses, which is a great start. Passwords are still the most widely relied-on security mechanism – and continue to be the weakest link in today’s enterprise security.  That needs to change. According to the Wall Street Journal, the World Wide Web Consortium has recently ratified a standard called WebAuthN, which allows websites to authenticate users with biometric information, or physical objects like security keys, and skip passwords altogether.

MobileIron is also taking a unique approach to this challenge by introducing zero sign-on (ZSO), built on the company’s unified endpoint management (UEM) platform and powered by the MobileIron Access solution. “By making mobile devices your identity, we create a world free from the constant pains of password recovery and the threat of data breaches due to easily compromised credentials,” wrote Simon Biddiscombe, MobileIron’s President and Chief Executive Officer in his recent blog post, Single sign-on is still one sign-on too many. Simon’s latest post MobileIron: We’re making history by making passwords history, provides the company’s vision going forward with ZSO. Zero sign-on eliminates passwords as the primary method for user authentication, unlike single sign-on, which still requires at least one username and password. MobileIron paved the way for a zero sign-on enterprise with its Access product in 2017, which enabled zero sign-on to cloud services on managed devices.

Conclusion

Mobile devices are the most quickly proliferating threat surface there are today and an integral part of everyone’s identities as well. Thwarting the many breach attempts attempted daily over mobile devices and across all threat surfaces needs to start with a solid Zero Trust framework. MobileIron’s introduction of zero sign-on (ZSO) eliminates passwords as the method for user authentication, replacing single sign-on, which still requires at least one username and password. ZSO is exactly what enterprises need to secure the proliferating number of mobile devices they rely on to operate and grow in a Zero Trust world.

CIO’s Guide To Stopping Privileged Access Abuse – Part 2

Why CIOs Are Prioritizing Privileged Credential Abuse Now

Enterprise security approaches based on Zero Trust continue to gain more mindshare as organizations examine their strategic priorities. CIOs and senior management teams are most focused on securing infrastructure, DevOps, cloud, containers, and Big Data projects to stop the leading cause of breaches, which is privileged access abuse.

Based on insights gained from advisory sessions with CIOs and senior management teams, Forrester estimates that 80% of data breaches have a connection to compromised privileged credentials, such as passwords, tokens, keys, and certificates. In another survey completed by Centrify, 74% of IT decision makers surveyed whose organizations have been breached in the past, say it involved privileged access abuse. Furthermore, 65% of organizations are still sharing root or privileged access to systems and data at least somewhat often. Centrify’s survey, Privileged Access Management in the Modern Threatscape, is downloadable here.

The following are the key reasons why CIOs are prioritizing privileged access management now:

  • Identities are the new security perimeter for any business, making privileged access abuse the greatest challenge CIOs face in keeping their businesses secure and growing. Gartner also sees privileged credential abuse as the greatest threat to organizations today, and has made Privileged Account Management one of the Gartner Top 10 Security Projects for 2018, and again in 2019Forrester and Gartner’s findings and predictions reflect the growing complexity of threatscapes every CIO must protect their business against while still enabling new business growth. Banking, financial services, and insurance (BFSI) CIOs often remark in my conversations with them that the attack surfaces in their organizations are proliferating at a pace that quickly scales beyond any trust but verify legacy approach to managing access. They need to provide applications, IoT-enabled devices, machines, cloud services, and human access to a broader base of business units than ever before.
  • CIOs are grappling with the paradox of protecting the rapidly expanding variety of attack surfaces from breaches while still providing immediate access to applications, systems, and services that support their business’ growth. CIOs I’ve met with also told me access to secured resources needs to happen in milliseconds, especially to support the development of new banking, financial services, and insurance applications in beta testing today, scheduled to be launched this summer. Their organizations’ development teams expect more intuitive, secure, and easily accessible applications than ever before, which is driving CIOs to prioritize privileged access management now
  • Adapting and risk-scoring every access attempt in real-time is key to customer experiences on new services and applications, starting with response times. CIOs need a security strategy that can flex or adapt to risk contexts in real-time, assessing every access attempt across every threat surface and generating a risk score in milliseconds. The CIOs I’ve met with regularly see a “never trust, always verify, enforce least privilege” approach to security as the future of how they’ll protect every threat surface from privileged access abuse. Each of their development teams is on tight deadlines to get new services launch to drive revenue in Q3. Designing in Zero Trust with a strong focus on Zero Trust Privilege is saving valuable development time now and is enabling faster authentication times of the apps and services in testing today.

Strategies For Stopping Privileged Credential Abuse – Part 2  

Recently I wrote a CIO’s Guide To Stopping Privileged Access Abuse – Part 1 detailing five recommended strategies for CIOs on how to stop privileged credential abuse. The first five strategies focus on the following: discovering and inventorying all privileged accounts; vaulting all cloud platforms’ Root Accounts; auditing privileged sessions and analyzing patterns to find privileged credential sharing not found during audits; enforcing least privilege access now within your existing infrastructure as much as possible; and adopting multi-factor authentication (MFA) across all threat surfaces that can adapt and flex to the risk context of every request for resources.

The following are the second set of strategies CIOs need to prioritize to further protect their organizations from privileged access abuse:

  1. After completing an inventory of privileged accounts, create a taxonomy of them by assigning users to each class or category, personalizing privileged credential access to the role and entitlement level for each. CIOs tell me this is a major time saver in scaling their Privileged Access Management (PAM) strategies. Assigning every human, machine and sensor-based identity is the goal with the overarching objective being the creation of a Zero Trust-based enterprise security strategy. Recommended initial classes or categories include IT administrators who are also responsible for endpoint security; developers who require occasional access to production instances; service desk teams and service operations; the Project Management Office (PMO) and project IT; and external contractors and consultants.
  2. By each category in the taxonomy, automate the time, duration, scope, resources, and entitlements of privileged access for each focusing on the estimated time to complete each typical task. Defining a governance structure that provides real-time access to resources based on successful authentication is a must-have for protecting privileged access credentials. By starting with the attributes of time, duration, scope and properties, organizations have a head start on creating a separation of duties (SOD) model. Separation of duties is essential for ensuring that privileged user accounts don’t have the opportunity to carry out and conceal any illegal or unauthorized activities.
  3. Using the taxonomy of user accounts created and hardened using the separation of duties model, automate privileged access and approval workflows for enterprise systems. Instead of having administrators approve or semi-automate the evaluation of every human- and machine-based request for access, consider automating the process with a request and approval workflow. With time, duration, scope, and properties of privileged access already defined human- and machine-based requests for access to IT systems and services are streamlined, saving hundreds of hours a year and providing a real-time log for audit and data analysis later.
  4. Break-glass, emergency or firecall account passwords need to be vaulted, with no exceptions. When there’s a crisis of any kind, the seconds it takes to get a password could mean the difference between cloud instances and entire systems being inaccessible or not. That’s why administrators often only manually secure root passwords to all systems, cloud platforms and containers included. This is the equivalent of leaving the front door open to the data center with all systems unlocked. The recent Centrify survey found that just 48% of organizations interviewed have a password vault. 52% are leaving the keys to the kingdom available for hackers to walk through the front door of data centers and exfiltraticate data whenever they want.
  5. Continuous delivery and deployment platforms including Ansible, Chef, Puppet, and others need to be configured when first installed to eliminate the potential for privileged access abuse. The CIOs whose teams are creating new apps and services are using Chef and Puppet to design and create workloads, with real-time integration needed with customer, pricing, and services databases and the systems they run on. Given how highly regulated insurance is, CIOs are saying they need to have logs that show activity down to the API level in case of an audit. The more regulated and audited a company, the more trusted and untrusted domains are seen as the past, Zero Trust as the future based on CIO’s feedback.

Conclusion

The CIOs I regularly meet with from the banking, financial services, and insurance industries are under pressure to get new applications and services launched while protecting their business’ daily operations. With more application and services development happening in their IT teams, they’re focusing on how they can optimize the balance between security and speed. New apps, services, and the new customers they attract are creating a proliferation of new threat surfaces, making every new identity the new security perimeter.

CIO’s Guide To Stopping Privileged Access Abuse – Part I

CIOs face the paradox of having to protect their businesses while at the same time streamlining access to the information and systems their companies need to grow. The threatscape they’re facing requires an approach to security that is adaptive to the risk context of each access attempt across any threat surface, anytime. Using risk scores to differentiate between privileged users attempting to access secured systems in a riskier context than normal versus privileged credential abuse by attackers has proven to be an effective approach for thwarting credential-based breaches.

Privileged credential abuse is one of the most popular breach strategies organized crime and state-sponsored cybercrime organizations use. They’d rather walk in the front door of enterprise systems than hack in. 74% of IT decision makers surveyed whose organizations have been breached in the past say it involved privileged access credential abuse, yet just 48% have a password vault. Just 21% have multi-factor authentication (MFA) implemented for privileged administrative access. These and many other insights are from Centrify’s recent survey, Privileged Access Management in the Modern Threatscape.

How CIOs Are Solving the Paradox of Privileged Credential Abuse

The challenge to every CIO’s security strategy is to adapt to risk contexts in real-time, accurately assessing every access attempt across every threat surface, risk-scoring each in milliseconds. By taking a “never trust, always verify, enforce least privilege” approach to security, CIOs can provide an adaptive, contextually accurate Zero Trust-based approach to verifying privileged credentials. Zero Trust Privilege is emerging as a proven framework for thwarting privileged credential abuse by verifying who is requesting access, the context of the request, and the risk of the access environment.

By taking a least privilege access approach, organizations can minimize attack surfaces, improve audit and compliance visibility, and reduce risk, complexity, and the costs of operating a modern, hybrid enterprise. CIOs are solving the paradox of privileged credential abuse by knowing that even if a privileged user has entered the right credentials but the request comes in with risky context, then stronger verification is needed to permit access.

Strategies For Stopping Privileged Credential Abuse

The following are five strategies CIOs need to concentrate on to stop privileged credential abuse. Starting with an inventory of privileged accounts and progressing through finding the gaps in IT infrastructure that create opportunities for privileged credential abuse, CIOs and their teams need to take preemptive action now to avert potential breaches in the future.

In Part 1 of a CIO’s Guide to Stopping Privileged Access Abuse, below are the steps they can take to get started:

  1. Discover and inventory all privileged accounts and their credentials to define who is accountable for managing their security and use. According to a survey by Gartner, more than 65% of enterprises are allowing shared use of privileged accounts with no accountability for their use. CIOs realize that a lack of consistent governance policies creates many opportunities for privileged credential abuse. They’re also finding orphaned accounts, multiple owners for privileged credentials and the majority of system administrators having super user or root user access rights for the majority of enterprise systems.
  2. Vault your cloud platforms’ Root Accounts and federate access to AWS, Google Cloud Platform, Microsoft Azure and other public cloud consoles. Root passwords on each of the cloud platforms your business relies on are the “keys to the kingdom” and provide bad actors from inside and outside the company to exfiltrate data with ease. The recent news of how a fired employee deleted his former employer’s 23 AWS servers is a cautionary tale of what happens when a Zero Trust approach to privileged credentials isn’t adopted. Centrify’s survey found that 63% or organizations take more than a day to shut off privilege access for an employee after leaving the company. Given how AWS root user accounts have the privilege to delete all instances immediately, it’s imperative for organizations to have a password vault where AWS root account credentials are stored. Instead of local AWS IAM accounts and access keys, use centralized identities (e.g., Active Directory) and enable federated login. By doing so, you obviate the need for long-lived access keys.
  3. Audit privileged sessions and analyze patterns to find potentially privileged credential sharing or abuse not immediately obvious from audits. Audit and log authorized and unauthorized user sessions across all enterprise systems, especially focusing on root password use across all platforms. Taking this step is essential for assigning accountability for each privileged credential in use. It will also tell you if privileged credentials are being shared widely across the organization. Taking a Zero Trust approach to securing privileged credentials will quickly find areas where there could be potential lapses or gaps that invite breaches. For AWS accounts, be sure to use AWS CloudTrail and Amazon CloudWatch to monitor all API activity across all AWS instances and your AWS account.
  4. Enforce least privilege access now within your existing infrastructure as much as possible, defining a security roadmap based on the foundations of Zero Trust as your future direction. Using the inventory of all privileged accounts as the baseline, update least privilege access on each credential now and implement a process for privilege elevation that will lower the overall risk and ability for attackers to move laterally and extract data. The days of “trust but verify” are over. CIOs from insurance and financial services companies recently spoken with point out that their new business models, all of them heavily reliant on secured Internet connectivity, are making Zero Trust the cornerstone of their future services strategies. They’re all moving beyond “trust but verify” to adopt a more adaptive approach to knowing the risk context by threat surface in real-time.
  5. Adopt multi-factor authentication (MFA) across all threat surfaces that can adapt and flex to the risk context of every request for resources. The CIOs running a series of insurance and financial services firms, a few of them former MBA students of mine, say multi-factor authentication is a must-have today for preventing privileged credential abuse. Their take on it is that adding in an authentication layer that queries users with something they know (user name, password, PIN or security question) with something they have (smartphone, one-time password token or smart card), something they are (biometric identification like fingerprint) and something they’ve done (contextual pattern matching of what they normally do where) has helped thwart privileged credential abuse exponentially since they adopted it. This is low-hanging fruit: adaptive MFA has made the productivity impact of this additional validation practically moot.

Conclusion

Every CIO I know is now expected to be a business strategist first, and a technologist second. At the top of many of their list of priorities is securing the business so it can achieve uninterrupted growth. The CIOs I regularly speak with running insurance and financial services companies often speak of how security is as much a part of their new business strategies as the financial products their product design teams are developing. The bottom line is that the more adaptive and able to assess the context of risks for each privilege access attempt a company’s access management posture can become, the more responsive they can be to employees and customers alike, fueling future growth.

5 Things Every Executive Needs To Know About Identity And Access Management

  • For new digital business models to succeed, customers’ privacy preferences need to be secure, and that begins by treating every identity as a new security perimeter.
  • Organizations need to recognize that perimeter-based security, which focuses on securing endpoints, firewalls, and networks, provides no protection against identity and credential-based threats. Until they start implementing identity-centric security measures, account compromise attacks will continue to provide a perfect camouflage for data breaches.
  • 74% of data breaches start with privileged credential abuse that could have been averted if the organizations had adopted a Privileged Access Management (PAM) strategy, according to a recent Centrify survey.
  • Just 48% of organizations have a password vault, and only 21% have multi-factor authentication (MFA) implemented for privileged administrative access.

New digital business models are redefining organizations’ growth trajectories and enabling startups to thrive, all driven by customer trust. Gaining and strengthening customer trust starts with a security strategy that can scale quickly to secure every identity and threat surface a new business model creates. Centrify’s recent survey, Privileged Access Management in the Modern Threatscape, found 74% of data breaches begin with privileged credential abuse. The survey also found that the most important areas of IT infrastructure that new digital business models rely on to succeed — including Big Data repositories, cloud platform access, containers, and DevOps — are among the most vulnerable. The most urgent challenges executives are facing include protecting their business, securing customer data, and finding new ways to add value to their business’ operations.

Why Executives Need to Know About Identity and Access Management Now  

Executives have a strong sense of urgency to improve Identity and Access Management (IAM) today to assure the right individuals access the right resources at the right times and for the right reasons. IAM components like Access Management, Single Sign-On, Customer Identity and Access Management (CIAM), Advanced Authentication, Identity Governance and Administration (IGA), IoT-Driven IAM, and Privileged Access Management address the need to ensure appropriate access to resources across an organization’s entire attack surface and to meet compliance requirements. Considering that privileged access abuse is the leading cause of today’s breaches, they’re especially prioritizing Privileged Account Management as part of their broader cybersecurity strategies to secure the “keys to their kingdom.” Gartner supports this view by placing a high priority on Privileged Account Management, including it in its Gartner Top 10 Security Projects for 2018, and again in 2019.

During a recent conversation with insurance and financial services executives, I learned why Privileged Access Management is such an urgent, high priority today. Privileged access abuse is the leading attack vector, where they see the majority of breach attempts to access the company’s most sensitive systems and data. It’s also where they can improve customer data security while also making employees more productive by giving them access systems and platforms faster. All of them know instances of hackers and state-sponsored hacking groups offering bitcoin payments in exchange for administrative-level logins and passwords to their financial systems.

Several of the executives I spoke with are also evaluating Zero Trust as the foundation for their cybersecurity strategy. As their new digital business models grow, all of them are focused on discarding the outdated, “trust, but verify” mindset and replacing it with Zero Trust, which mandates a “never trust, always verify” approach. They’re also using a least privilege access approach to minimize each attack surface and improve audit and compliance visibility while reducing risk, complexity, and costs.

The following are the five things every executive needs to know about Identity and Access Management to address a reality that every company and consumer must recognize exists today: attackers no longer “hack” in, they log in.

  1. Designing in the ability to manage access rights and all digital identities of privileged users require Privileged Access Management (PAM) and Identity Governance and Administration (IGA) systems be integrated as part of an IAM strategy. For digital business initiatives’ security strategies to scale, they need to support access requests, entitlement management, and user credential attestation for governance purposes. With identities being the new security perimeter, provisioning least privileged access to suppliers, distributors, and service organizations is also a must-have to scale any new business model. Natively, IGA is dealing only with end users – not privileged users. Therefore integration with PAM systems is required to bring in privileged user data and gain a holistic view of access entitlements.
  2. IAM is a proven approach to securing valuable Intellectual Property (IP), patents, and attaining regulatory compliance, including GDPR. The fascinating digital businesses emerging today also function as patent and IP foundries. A byproduct of their operations is an entirely new business, product and process ideas. Executives spoken with are prioritizing how they secure intellectual property and patents using an Identity and Access Management strategy.
  3. Knowing with confidence the identity of every user is what makes every aspect of an IAM strategy work. Having Multi-Factor Authentication (MFA) enabled for every access session, and threat surface is one of the main processes that make an IAM strategy succeed. It’s a best practice to reinforce Zero Trust principles through multi-factor authentication enforcement on each computer that cannot be circumvented (or bypassed) by malware.
  4. Designing in transaction verification now for future e-commerce digital business models is worth it. Think of your IAM initiative as a platform to create ongoing customer trust with. As all digital business initiatives rely on multi-channel selling, designing in transaction verification as part of an IAM strategy is essential. Organizations are combining verification and MFA to thwart breaches and the abuse of credential access abuse.
  5. In defining any IAM strategy focus on how Privileged Access Management (PAM) needs to be tailored to your specific business needs. PAM is the foundational element that turns the investments made in security into business value. It’s a catalyst for ensuring customer trust turns into revenue. Many organizations equate PAM with a password vault. But in a modern threatscape where humans, machines, applications, and services dynamically require access to a broadening range of attack surfaces such as cloud, IoT, Big Data, and containers, that outdated legacy approach won’t effectively secure the leading attack vector: privileged access abuse. Vendors such as Centrify and others are looking beyond the vault and offering Zero Trust solutions for PAM that address these modern access requestors and attack surfaces.

Conclusion

Insurance and financial services executives realize, and even predict, that there’s going to be an increase in the number and intensity of efforts to break into their systems using compromised credentials. Prioritizing Privileged Access Management as part of the IAM toolkit is proving to be an effective cybersecurity strategy for protecting their businesses and customers’ data while also making a valuable contribution to its growth. The bottom line is that Identity and Access Management is the cornerstone of any effective Zero Trust-based strategy, and taking an aggressive, pre-emptive approach to Privileged Access Management is the new normal for organizations’ cybersecurity strategies.

5 Ways To Demystify Zero Trust Security

Bottom Line: Instead of only relying on security vendors’ claims about Zero Trust, benchmark them on a series of five critical success factors instead, with customer results being key.

Analytics, Zero Trust Dominated RSA

Analytics dashboards dominated RSA from a visual standpoint, while Zero Trust Security reigned from an enterprise strategy one. Over 60 vendors claimed to have Zero Trust Security solutions at RSA, with each one defining the concept in a slightly different way.

RSA has evolved into one of the highest energy enterprise-focused conferences today, and in 2019 Zero Trust was center stage in dozens of vendor booths. John Kindervag created the Zero Trust Security framework while at Forrester in 2010. Chase Cunningham, who is a Principal Analyst at Forrester today, is a leading authority on Zero Trust and frequently speaks and writes on the topic. Be sure to follow his blog to stay up to date with his latest research. His most recent post, OK, Zero Trust Is An RSA Buzzword — So What?, captures the current situation on Zero Trust perfectly. Becca Chambers’ blog post, Talking All Things Zero Trust at RSA Conference 2019, includes an insightful video of how the conferences’ attendees define Zero Trust.

With so many vendors claiming to offer Zero Trust solutions, how can you tell which ones have enterprise-ready, scalable solutions?  The following are five ways to demystify Zero Trust:

  1. Customer references are willing to talk and case studies available. With the ambitious goal of visiting every one of the 60 vendors who claimed to have a Zero Trust solution at RSA, I quickly realized that there’s a dearth of customer references. To Chase Cunningham’s point, more customer use cases need to be created, and thankfully that’s on his research agenda. Starting the conversation with each vendor visited by asking for their definition of Zero Trust either led to a debate of whether Zero Trust was needed in the industry or how their existing architecture could morph to fit the framework. Booth staffs at the following companies deserve to be commended for how much they know about their customers’ success with Zero Trust: AkamaiCentrifyCiscoMicrosoftMobileIronPalo Alto NetworksSymantec, and Trend Micro. The team at Ledios Cyberwho was recently acquired by Capgemini, was demonstrating how Zero Trust applied to Industrial Control Systems and shared a wealth of customer insights as well.
  2. Defines success by their customers’ growth, stability and earned trust instead of relying on fear. A key part of de-mystifying Zero Trust is seeing how effective vendors are at becoming partners on the journey their customers are on. While in the Centrify booth I learned of how Interval International has been able to implement a least privilege model for employees, contractors, and consultants, streamline user onboarding, and enable the company to continue its rapid organic growth. At MobileIron, I learned how NASDAQ is scaling mobile applications including CRM to their global sales force on a Zero Trust platform. The most customer-centric Zero Trust vendors tend to differentiate on earned trust over selling fear.
  3. Avoid vendors who have a love-hate relationship with Zero Trust. Zero Trust is having an energizing effect on the security landscape as it provides vendors with a strategic framework they can differentiate themselves in. Security vendors are capitalizing on the market value right now, with product management and engineering teams working overtime to get new applications and platforms ready for market. I found a few vendors who have a love-hate relationship with Zero Trust. They love the marketing mileage or buzz, yet aren’t nearly as enthusiastic about changing product and service strategies. If you’re looking for Zero Trust solutions, be sure to watch for this and find a vendor who is fully committed.
  4. Current product strategies and roadmaps reflect a complete commitment to Zero Trust. Product demos at RSA ranged from supporting the fundamentals of Zero Trust to emulating its concepts on legacy architectures. One of the key attributes to look for is how perimeterless a given security application is that claims to support Zero Trust. How well can a given application protect mobile devices? An IoT device? How can a given application or security platform scale to protect privileged credentials? These are all questions to ask of any vendor who claims to have a Zero Trust solution. Every one of them will have analytics options; the question is whether they fit with your given business scenario. Finally, ask to see how Zero Trust can be automated across all user accounts and how privileged access management can be scaled using Identity Access Management systems including password vaults and Multi-Factor Authentication (MFA).
  5. A solid API strategy for scaling their applications and platforms with partner successes that prove it. One of the best questions to gauge the depth of commitment any vendor has to Zero Trust is to ask about their API strategy. It’s interesting to hear how vendors with Zero Trust-based product and services strategies are scaling inside their largest customers using APIs. Another aspect of this is to see how many of their services, system integration, technology partners are using their APIs to create customized solutions for customers. Success with an API strategy is a leading indicator of how reliably any Zero Trust vendor will be able to scale in the future.

Conclusion

RSA is in many ways a microcosm of the enterprise security market in general and Zero Trust specifically. The millions of dollars in venture capital invested in security analytics and Zero Trust made it possible for vendors to create exceptional in-booth experiences and demonstrations – much the same way venture investment is fueling many of their roadmaps and sales teams. Zero Trust vendors will need to provide application roadmaps that show their ability to move beyond prevention of breaches to more prediction, at the same time supporting customers’ needs to secure infrastructure, credentials, and systems to ensure uninterrupted growth.

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