Skip to content

Posts tagged ‘MobileIron’

Predicting How AI Will Improve Talent Management In 2020

Predicting How AI Will Improve Talent Management In 2020

47% of U.S.-based enterprises are using AI today for recruitment, leading all countries in the survey. U.S.-based enterprises’’ adoption of AI for recruitment soared in the last year, jumping from 22% in 2018 to 47% this year based on last years’ Harris Interactive Talent Intelligence and Management Report 2018.

  • 73% of U.S. CEOs and CHROs plan to use more AI in the next three years to improve talent management.
  • U.S.-based enterprises’’ adoption of AI for recruitment soared in the last year, jumping from 22% in 2018 to 47% this year.
  • U.S.-based enterprises lead in the use of AI to automate repetitive tasks (44%) and employee retention (42%).

These and many other fascinating insights are from a recent study completed by Harris Interactive in collaboration with Eightfold titled Talent Intelligence And Management Report 2019-2020, which provides insights into how CHROs are adopting AI today and in the future. You can download a copy here. A total of 1,350 CEOs and CHROs from the U.S., France, Germany, and the U.K. responded to the survey. One of the most noteworthy findings is how U.S-based CEOs and CHROs lead the world in prioritizing and taking action on improving their teams and their own AI skills. The more expertise they and their teams have with AI, the more effective they will be achieving operational improvements while taming the bias beast. The following graphic provides insights into how the four nations surveyed vary by their CEOs’ and CHROs’ perception of new technologies having had positive impacts, their plans for using AI in three years, and employee’s concerns about AI:

Predicting How AI Will Improve Talent Management In 2020

Predicting The Future Of AI In Talent Management

Four leading experts who are actively advising clients, implementing, and using AI to solve talent management challenges shared their predictions of how AI will improve talent management in 2020. The panel includes Kelly O. Kay, Partner, Heidrick & Struggles, Jared Lucas, Chief People Officer at MobileIron, Mandy Sebel, Senior Vice President, People at UiPath and David Windley CEO, IQTalent Partners. Mr. Kay leads the Software Practice for Heidrick & Struggles, a leading executive search and consulting firm commented: “As we all know, the talent crisis of 2019 is real and Eightfold’s application of AI on today is the most impactful approach I’ve seen and the outcomes they deliver eliminate unconscious bias, increases transparency and improves matching supply and demand of talent.” The following are their predictions of how AI will improve the following areas of talent management in 2020:

  • “Pertaining to talent attraction & acquisition-as adoption of intelligent automation and AI tools increases hiring managers and recruiters more easily uncover and surface overlooked talent pools,” said Mandy Sebel, Senior Vice President, People at UiPath.
  • “I predict that AI will become a requirement for companies in the screening of candidates due to the pervasive need to find higher-quality candidates at a faster pace,” said Jared Lucas, Chief People Officer at MobileIron.
  • “I believe the use of AI in the talent acquisition space will begin to hit critical mass in 2020. We are still in the early adopter phase, but the use of AI to match potential candidates to job profiles is catching on. Especially the use of AI for rediscovering candidates in ATS systems of larger corporations. Companies like Eightfold, Hiretual, and Atipica are leading the way,” said David Windley CEO, IQTalent Partners.
  • “Fear of job replacement will also subside, and more focus on job/role evolution as teams are experiencing firsthand how respective task elimination allows them to do more meaningful work,” commented Mandy Sebel, Senior Vice President, People at UiPath.
  • AI will provide the insights needed for CHROs to retain and grow their best talent, according to Jared Lucas, Chief People Officer at MobileIron. “I predict that AI will drive better internal mobility and internal candidate identification as companies are better able to mine their internal talent to fill critical roles,” he said.
  • Having gained credibility for executive and senior management recruiting, AI platforms’ use will continue to proliferate in 2020. “Private Equity is beginning to commercialize how AI can help select executives for roles based on competencies and experiences, which is exciting!” said Kelly O. Kay, Partner, Heidrick & Struggles.

10 Predictions How AI Will Improve Cybersecurity In 2020

10 Predictions How AI Will Improve Cybersecurity In 2020

Capgemini predicts 63% of organizations are planning to deploy AI in 2020 to improve cybersecurity, with the most popular application being network security.

Cybersecurity is at an inflection point entering 2020. Advances in AI and machine learning are accelerating its technological progress. Real-time data and analytics are making it possible to build stronger business cases, driving higher adoption. Cybersecurity spending has rarely been linked to increasing revenues or reducing costs, but that’s about to change in 2020.

What Leading Cybersecurity Experts Are Predicting For 2020

Interested in what the leading cybersecurity experts are thinking will happen in 2020, I contacted five of them. Experts I spoke with include Nicko van Someren, Ph.D. and Chief Technology Officer at Absolute Software; Dr. Torsten George, Cybersecurity Evangelist at Centrify; Craig Sanderson, Vice President of Security Products at Infoblox; Josh Johnston, Director of AI, Kount; and Brian Foster, Senior Vice President Product Management at MobileIron. Each of them brings a knowledgeable, insightful, and unique perspective to how AI and machine learning will improve cybersecurity in 2020. The following are their ten predictions:

  1. AI and machine learning will continue to enable asset management improvements that also deliver exponential gains in IT security by providing greater endpoint resiliency in 2020. Nicko van Someren, Ph.D. and Chief Technology Officer at Absolute Software, observes that “Keeping machines up to date is an IT management job, but it’s a security outcome. Knowing what devices should be on my network is an IT management problem, but it has a security outcome. And knowing what’s going on and what processes are running and what’s consuming network bandwidth is an IT management problem, but it’s a security outcome. I don’t see these as distinct activities so much as seeing them as multiple facets of the same problem space, accelerating in 2020 as more enterprises choose greater resiliency to secure endpoints.”
  2. AI tools will continue to improve at drawing on data sets of wildly different types, allowing the “bigger picture” to be put together from, say, static configuration data, historic local logs, global threat landscapes, and contemporaneous event streams.  Nicko van Someren, Ph.D., and CTO at Absolute Software also predict that“Enterprise executives will be concentrating their budgets and time on detecting cyber threats using AI above predicting and responding. As enterprises mature in their use and adoption of AI as part of their cybersecurity efforts, prediction and response will correspondingly increase.”
  3. Threat actors will increase the use of AI to analyze defense mechanisms and simulate behavioral patterns to bypass security controls, leveraging analytics to and machine learning to hack into organizations. Dr. Torsten George, Cybersecurity Evangelist at Centrify, predicts that “threat actors, many of them state-sponsored, will increase their use and sophistication of AI algorithms to analyze organizations’’ defense mechanisms and tailor attacks to specific weak areas. He also sees the threat of bad actors being able to plug into the data streams of organizations and use the data to further orchestrate sophisticated attacks.”
  4. Given the severe shortage of experienced security operations resources and the sheer volume of data that most organizations are trying to work through, we are likely to see organizations seeking out AI/ML capabilities to automate their security operations processes. Craig Sanderson, Vice President of Security Products at Infoblox also predicts that “while AI and machine learning will increasingly be used to detect new threats it still leaves organizations with the task of understanding the scope, severity, and veracity of that threat to inform an effective response. As security operations becomes a big data problem it necessitates big data solutions.”
  5. There’s going to be a greater need for adversarial machine learning to combat supply chain corruption in 2020. Sean Tierney, Director of Threat Intelligence at Infoblox, predicts that “the need for adversarial machine learning to combat supply chain corruption is going to increase in 2020. Sean predicts that the big problem with remote coworking spaces is determining who has access to what data. As a result, AI will become more prevalent in traditional business processes and be used to identify if a supply chain has been corrupted.”
  6. Artificial intelligence will become more prevalent in account takeover—both the proliferation and prevention of it. Josh Johnston, Director of AI at Kount, predicts that “the average consumer will realize that passwords are not providing enough account protection and that every account they have is vulnerable. Captcha won’t be reliable either, because while it can tell if someone is a bot, it can’t confirm that the person attempting to log in is the account holder. AI can recognize a returning user. AI will be key in protecting the entire customer journey, from account creation to account takeover, to a payment transaction. And, AI will allow businesses to establish a relationship with their account holders that are protected by more than just a password.”
  7. Consumers will take greater control of their data sharing and privacy in 2020. Brian Foster, Senior Vice President Product Management at MobileIron, observes that over the past few years, we’ve witnessed some of the biggest privacy and data breaches. As a result of the backlash, tech giants such as Apple, Google, Facebook and Amazon beefed up their privacy controls to gain back trust from customers. Now, the tables have turned in favor of consumers and companies will have to put privacy first to stay in business. Moving forward, consumers will own their data, which means they will be able to selectively share it with third parties, but most importantly, they will get their data back after sharing, unlike in years past.
  8. As cybersecurity threats evolve, we’ll fight AI with AI. Brian Foster, Senior Vice President Product Management at MobileIron, notes that the most successful cyberattacks are executed by highly professional criminal networks that leverage AI and ML to exploit vulnerabilities such as user behavior or security gaps to gain access to valuable business systems and data. All of this makes it extremely hard for IT security organizations to keep up — much less stay ahead of these threats. While an attacker only needs to find one open door in an enterprise’s security, the enterprise must race to lock all of the doors. AI conducts this at a pace and thoroughness human ability can no longer compete with, and businesses will finally take notice in 2020.
  9. AI and machine learning will thwart compromised hardware finding its way into organizations’ supply chains. Rising demand for electronic components will expand the market for counterfeit components and cloned products, increasing the threat of compromised hardware finding its way into organizations’ supply chains. The vectors for hardware supply-chain attacks are expanding as market demand for more and cheaper chips, and components drive a booming business for hardware counterfeiters and cloners. This expansion is likely to create greater opportunities for compromise by both nation-state and cybercriminal threat actors. Source: 2020 Cybersecurity Threats Trends Outlook; Booz, Allen, Hamilton, 2019.
  10. Capgemini predicts 63% of organizations are planning to deploy AI in 2020 to improve cybersecurity, with the most popular application being network security. Capgemini found that nearly one in five organizations were using AI to improve cybersecurity before 2019. In addition to network security, data security, endpoint security, and identity and access management are the highest priority use cases for improving cybersecurity with AI in enterprises today. Source: Capgemini, Reinventing Cybersecurity with Artificial Intelligence: The new frontier in digital security.
10 Predictions How AI Will Improve Cybersecurity In 2020

Source: Capgemini, Reinventing Cybersecurity with Artificial Intelligence: The new frontier in digital security.

What’s New On The Zero Trust Security Landscape In 2019

What’s New On The Zero Trust Security Landscape In 2019

  • Forrester added in Checkpoint, Forescout, Google, illumio, MobileIron, Proofpoint, Symantec, and Unisys in their latest Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers this year.
  • Forrester’s 2019 scorecard increased the weight on network security, automation and orchestration, and portfolio growth rate compared to last year, adding in Zero Trust eXtended (ZTX) ecosystem advocacy to the scorecard for the first time.
  • Microsoft and VMWare are no longer included in the Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers this year.

These and many other interesting insights are from what’s new in the Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q4 2019, written by Chase Cunningham and published on October 29, 2019. Chase is a leading authority on Zero Trust Security, and I was fortunate to have the opportunity to interview him earlier this year. You can read the interview here,10 Questions With Chase Cunningham On Cybersecurity. Forrester included 14 vendors in this assessment: Akamai Technologies, Check Point, Cisco, Cyxtera Technologies, Forcepoint, Forescout, Google, illumio, MobileIron, Okta, Palo Alto Networks, Proofpoint, Symantec, and Unisys. The following is the Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 graphic from the free reprint offered by MobileIron here.

Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q4 2019

 

Summary of What’s New In Forrester’s Zero Trust Wave This Year

The latest Forrester Wave adds in and places high importance on Zero Trust eXtended (ZTX) ecosystem advocacy, allocating 25% of the weight associated with the Strategy section on the scorecard. Forrester sees Zero Trust as a journey, with vendors who provide the greatest assistance and breadth of benefits on a unified platform being the most valuable. The Wave makes it clear that Zero Trust doesn’t refer to a specific technology but rather the orchestration of several technologies to enable and strengthen their Zero Trust framework. Key insights from what’s new this year in the Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 include the following:

  • Platforms are powering the Zero Trust landscape and delivering the greatest value to organizations on their Zero Trust journey. Forrester notes that organizations are getting the greatest benefits from choosing a single vendor who can deliver integrated, real-world capabilities instead of marketing hype.
  • Ease of use and excellent usability need to be the new normal when it comes to Zero Trust Solutions. Forrester sees a widening gap between Zero Trust solutions that take administrator and end-user experience into account and deliver the critical capabilities that make ZTX frameworks successful and those that don’t. It’s common knowledge of how challenging Zero Trust solutions and platforms are to deploy. Raising the issue of improving usability will help expand the total available market for Zero Trust solutions and increase the effectiveness of every platform installed.
  • A much stronger focus on Application Programmer Interfaces (APIs) and integration. This year’s Wave places much greater emphasis on APIs and the need to integrate every application and Web Service across a Zero Trust platform. The greater the integration expertise of any Zero Trust vendor, the faster an organization adopting their systems and platforms will attain secured stability across every threat surface.
  • Forrester advises Zero Trust vendors to concentrate on four key aspects of their strategy if they’re going to deliver overwhelming value to organizations they’re selling to. These four key aspects include actively advocating for Zero Trust as evidenced by driving product strategies that prioritize needed capabilities; supporting micro-segmentation; enforcing policy everywhere by first enabling extensive, proven integrations using well-documented and tested APIs that make it possible to enable policy definition and enforcement across enterprises; and provide identity beyond identity and access management (IAM).
  • Cyxtera Technologies, MobileIron, and Proofpoint are new to the Zero Trust World, each bringing valuable contributions to enterprises on their Zero Trust journey. Of the three, MobileIron is the most noteworthy as their approach to Zero Trust begins with the device and scales across mobile infrastructures. Forrester observes that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees all three vendors as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future.

Conclusion

The latest Forrester Wave™: Zero Trust eXtended Ecosystem Platform Providers, Q4 2019, reflects the growing maturity of the Zero Trust eXtended (ZTX) Ecosystem. Adding in Zero Trust eXtended (ZTX) ecosystem advocacy and weighing it at 25% reflects how serious Forrester is about evaluating vendors on solid, real product features over marketing claims. The increased focus on platforms, APIs and integration also reflect the growing maturity of enterprises adopting Zero Trust frameworks today.

Financial Services Rely On BYOD – How Do They Stay Secure?

Financial Services Rely On BYOD – How Do They Stay Secure?

Bottom Line: 2020 is going to be the year companies launch more digital business initiatives that depend on BYOD than ever before, making Zero Trust Security a key contributor to their success.

Financial Services firms are at an inflection point going into 2020. Mobile-first products and services now dominate their product roadmaps for next year, with applications’ speed and security being paramount. In fintech, DevOps teams have been working with AngularJS for years now, and the scale and speed of their applications reflect their expertise. How well existing IT infrastructure flexes to support the new mobile-first product and services strategies depends on how quickly members of IT, customer service, and customer success teams can respond. BYOD is proving invaluable in achieving the speed of response these new digital business models require.

In 2020 more employees of Financial Services firms will rely on their mobile devices as their primary form of digital ID than has ever been the case before. A recent survey conducted by IDG in association with MobileIron found that 89% of security leaders believe mobile devices will be the primary digital ID employees use to gain access to resources and get work done. The CIOs I’ve spoken agree. A copy of the IDG and MobileIron study, Say Goodbye to Passwords, can be downloaded here.

Counting On BYOD To Deliver Responsiveness And Speed

CIO and IT bonuses are often indexed to the revenue contributions their new products and services deliver, making speed, scale, security, and responsiveness the most important features of all. Fintech CIOs are saying that BYOD is proving indispensable in scaling IT in support of new digital business initiatives as a result. By 2022, 75% of smartphones used in the enterprise will bring your own device (BYOD), up from 35% in 2018, forcing a migration from device-centric management to app- and data-centric management, according to Gartner’s Competitive Landscape: Managed Mobility Services.

Two factors continue to propel BYOD adoption in financial services, fueling the need for Zero Trust Security across every mobile device. The first is the need for real-time responsiveness from internal team members and the second is having every threat surface protected without degrading the time to respond to customers. Every CIO, IT and Product Management leader I’ve spoken with mention the race they are in to deliver mobile-first products and services early in 2020 that redefine their business.  With every identity being a new security perimeter, Financial Services firms are relying on Unified Endpoint Management (UEM), multi-factor authentication (MFA), and additional zero trust-enabling technologies as an integral part of their Enterprise Mobility Management (EMM) strategy. Their goal is to create a Zero Trust Security framework that protects every mobile device endpoint. Leaders in this field include MobileIron, who also provides zero sign-on (ZSO), and mobile threat defense (MTD) in addition to UEM and EMM solutions today.  The following are the key features every BYOD program needs to offer to stay secure, scale and succeed in 2020:

  •  Separation of business and personal data is a must-have in any BYOD security strategy. FinTechs who have the greatest success with BYOD as part of their digital initiatives are relying on Enterprise Mobility Management (EMM) to selectively wipe only the business data from a device in the event it is compromised.
  • An interactive, intuitive user experience that can be quickly customized at scale by role, department, and workflow requirements without impacting user productivity. Too often BYOD users have had to trade off having stronger security on their own devices versus using a company-provided smartphone to get remote work done. The best EMM and UEM solutions in the market today enable Zero Trust by treating every identity as a new security perimeter.
  • Define the success of a BYOD security strategy by how well it immediately shuts down access to confidential data and systems first. Being able to immediately block access to confidential systems and data is the most important aspect of securing any BYOD across a network.
  • Limit access to internal system resources based on the employee’s department, role, and function to eliminate the risk of confidential data ending up in a personal app. EMM solutions have progressed quickly, especially on the dimension of providing Zero Trust Security across BYOD networks. Look for an EMM solution that gives the administrator the flexibility of limiting mobile device access to a specific series of services and access points based on an employees’ role in a specific department and the scope of data they need access to.
  • Proven multi-operating system expertise and support for legacy internally created mobile applications and services. One of the main reasons BYOD is succeeding today as an enablement strategy is the freedom it gives users to select the device they prefer to work with. Supporting Android and IOS is a given. Look for advanced EMM and UEM solutions that also support legacy mobility applications. The best BYOD security solutions deliver device and application compatibility with no degradation in security or performance.

Conclusion – Why BYOD Strategies Need Zero Trust Now

Trust-but-verify isn’t working today. Attackers are capitalizing on it by stealing or buying privileged access credentials, accessing any system or database they choose. Financial Services firms fully expect their new products and services launching in 2020 to face an onslaught of breach and hacking attempts. Trust-but-verify approaches that are propagated across an enterprises’ BYOD base of devices using Virtual Private Networks and demilitarized zones (DMZ) impede employee’s productivity, often force login authentication. Trust-but verify doesn’t scale well into BYOD scenarios, leaving large gaps attackers can gain access to valuable internal data and systems. For BYOD users, trust-but-verify reduces productivity, delivers poor user experiences, and for new business models, slower customer response times.

By going to a Zero Trust Framework, Financial Services firms will be able to treat every identity and the mobile device they are using as their new security perimeter. Basing a BYOD strategy on a Zero Trust Framework enables any organization to find the correlation between the user, device, applications, and networks in milliseconds, thwarting potential threats before granting secure access to the device. Leaders delivering Zero Trust for BYOD include MobileIron, who provides endpoint management (UEM) capabilities with enabling technologies of zero sign-on (ZSO) user and device authentication, multi-factor authentication (MFA), and mobile threat detection (MTD).

10 Ways AI And Machine Learning Are Improving Endpoint Security

  • Gartner predicts $137.4B will be spent on Information Security and Risk Management in 2019, increasing to $175.5B in 2023, reaching a CAGR of 9.1%. Cloud Security, Data Security, and Infrastructure Protection are the fastest-growing areas of security spending through 2023.
  •  69% of enterprise executives believe artificial intelligence (AI) will be necessary to respond to cyberattacks with the majority of telecom companies (80%) saying they are counting on AI to help identify threats and thwart attacks according to Capgemini.
  •  Spending on AI-based cybersecurity systems and services reached $7.1B in 2018 and is predicted to reach $30.9B in 2025, attaining a CAGR of 23.4% in the forecast period according to Zion Market Research.

Traditional approaches to securing endpoints based on the hardware characteristics of a given device aren’t stopping breach attempts today. Bad actors are using AI and machine learning to launch sophisticated attacks to shorten the time it takes to compromise an endpoint and successfully breach systems. They’re down to just 7 minutes after comprising an endpoint and gaining access to internal systems ready to exfiltrate data according to Ponemon. The era of trusted and untrusted domains at the operating system level, and “trust, but verify” approaches are over. Security software and services spending is soaring as a result, as the market forecasts above show.

AI & Machine Learning Are Redefining Endpoint Security

AI and machine learning are proving to be effective technologies for battling increasingly automated, well-orchestrated cyberattacks and breach attempts. Attackers are combining AI, machine learning, bots, and new social engineering techniques to thwart endpoint security controls and gain access to enterprise systems with an intensity never seen before. It’s becoming so prevalent that Gartner predicts that more than 85% of successful attacks against modern enterprise user endpoints will exploit configuration and user errors by 2025. Cloud platforms are enabling AI and machine learning-based endpoint security control applications to be more adaptive to the proliferating types of endpoints and corresponding threats. The following are the top ten ways AI and machine learning are improving endpoint security:

  • Using machine learning to derive risk scores based on previous behavioral patterns, geolocation, time of login, and many other variables is proving to be effective at securing and controlling access to endpoints. Combining supervised and unsupervised machine learning to fine-tune risk scores in milliseconds is reducing fraud, thwarting breach attempts that attempt to use privileged access credentials, and securing every identity on an organizations’ network. Supervised machine learning models rely on historical data to find patterns not discernable with rules or predictive analytics. Unsupervised machine learning excels at finding anomalies, interrelationships, and valid links between emerging factors and variables. Combining both unsupervised and supervised machine learning is proving to be very effective in spotting anomalous behavior and reducing or restricting access.
  • Mobile devices represent a unique challenge to achieving endpoint security control, one that machine learning combined with Zero Trust is proving to be integral at solving.  Cybercriminals prefer to steal a mobile device, its passwords, and privileged access credentials than hack into an organization. That’s because passwords are the quickest onramp they have to the valuable data they want to exfiltrate and sell. Abandoning passwords for new techniques including MobileIron’s zero sign-on approach shows potential for thwarting cybercriminals from getting access while hardening endpoint security control. Securing mobile devices using a zero-trust platform built on a foundation of unified endpoint management (UEM) capabilities enables enterprises to scale zero sign-on for managed and unmanaged services for the first time. Below is a graphic illustrating how they’re adopting machine learning to improve mobile endpoint security control:
  • Capitalizing on the core strengths of machine learning to improve IT asset management is making direct contributions to greater security.  IT Management and security initiatives continue to become more integrated across organizations, creating new challenges to managing endpoint security across each device. Absolute Software is taking an innovative approach to solve the challenge of improving IT asset management, so endpoint protection is strengthened at the same time. Recently I had a chance to speak with Nicko van Someren, Ph.D. and Chief Technology Officer at Absolute Software, where he shared with me how machine learning algorithms are improving security by providing greater insights into asset management. “Keeping machines up to date is an IT management job, but it’s a security outcome. Knowing what devices should be on my network is an IT management problem, but it has a security outcome. And knowing what’s going on and what processes are running and what’s consuming network bandwidth is an IT management problem, but it’s a security outcome. I don’t see these as distinct activities so much as seeing them as multiple facets of the same problem space. Nicko added that Absolute’s endpoint security controls begin at the BIOS level of over 500M devices that have their endpoint code embedded in them. The Absolute Platform is comprised of three products: Persistence, Intelligence, and Resilience—each building on the capabilities of the other. Absolute Intelligence standardizes the data around asset analytics and security advocacy analytics to allow Security managers to ask any question they want. (“What’s slowing down my device? What’s working and what isn’t? What has been compromised? What’s consuming too much memory? How does this deviate from normal performance?”). An example of Absolute’s Intelligence providing insights into asset management and security is shown below:
  • Machine learning has progressed to become the primary detection method for identifying and stopping malware attacks. Machine learning algorithms initially contributed to improving endpoint security by supporting the back-end of malware protection workflows. Today more vendors are designing endpoint security systems with machine learning as the primary detection method. Machine learning trained algorithms can detect file-based malware and learn which files are harmful or not based on the file’s metadata and content. Symantec’s Content & Malware Analysis illustrates how machine learning is being used to detect and block malware. Their approach combines advanced machine learning and static code file analysis to block, detect, and analyze threats and stop breach attempts before they can spread.
  • Supervised machine learning algorithms are being used for determining when given applications are unsafe to use, assigning them to containers, so they’re isolated from production systems. Taking into account an applications’ threat score or reputation, machine learning algorithms are defining if dynamic application containment needs to run for a given application. Machine learning-based dynamic application containment algorithms and rules block or log unsafe actions of an application based on containment and security rules. Machine learning algorithms are also being used for defining predictive analytics that define the extent of a given applications’ threat.
  •  Integrating AI, machine learning, and SIEM (Security Information and Event Management) in a single unified platform are enabling organizations to predict, detect, and respond to anomalous behaviors and events. AI and machine learning-based algorithms and predictive analytics are becoming a core part of SIEM platforms today as they provide automated, continuous analysis and correlation of all activity observed within a given IT environment. Capturing, aggregating, and analyzing endpoint data in real-time using AI techniques and machine learning algorithms is providing entirely new insights into asset management and endpoint security. One of the most interesting companies to watch in this area is LogRhythm. They’ve developed an innovative approach to integrating AI, machine learning, and SIEM in their LogRhythm NextGen SIEM Platform, which delivers automated, continuous analysis and correlation of all activity observed within an IT environment. The following is an example of how LogRhythm combines AI, machine learning, and SIEM to bring new insights into securing endpoints across a network.
  • Machine learning is automating the more manually-based, routine incident analysis, and escalation tasks that are overwhelming security analysts today. Capitalizing on supervised machine learnings’ innate ability to fine-tune algorythms in milliseconds based on the analysis of incidence data, endpoint security providers are prioritizing this area in product developnent. Demand from potential customers remains strong, as nearly everyone is facing a cybersecurity skills shortage while facing an onslaught of breach attempts.  “The cybersecurity skills shortage has been growing for some time, and so have the number and complexity of attacks; using machine learning to augment the few available skilled people can help ease this. What’s exciting about the state of the industry right now is that recent advances in Machine Learning methods are poised to make their way into deployable products,” Absolute’s CTO Nicko van Someren added.
  • Performing real-time scans of all processes with an unknown or suspicious reputation is another way how machine learning is improving endpoint security. Commonly referred to as Hunt and Respond, supervised and unsupervised machine learning algorithms are being used today to seek out and resolve potential threats in milliseconds instead of days. Supervised machine learning algorithms are being used to discover patterns in known or stable processes where anomalous behavior or activity will create an alert and pause the process in real-time. Unsupervised machine learning algorithms are used for analyzing large-scale, unstructured data sets to categorize suspicious events, visualize threat trends across the enterprise, and take immediate action at a single endpoint or across the entire organization.
  • Machine learning is accelerating the consolidation of endpoint security technologies, a market dynamic that is motivating organizations to trim back from the ten clients they have on average per endpoint today. Absolute Software’s 2019 Endpoint Security Trends Report found that a typical device has ten or more endpoint security agents installed, each often conflicting with the other. The study also found that enterprises are using a diverse array of endpoint agents, including encryption, AV/AM, and Endpoint Detection and Response (EDR). The wide array of endpoint solutions make it nearly impossible to standardize a specific test to ensure security and safety without sacrificing speed. By helping to accelerate the consolidation of security endpoints, machine learning is helping organizations to see the more complex and layered the endpoint protection, the greater the risk of a breach.
  • Keeping every endpoint in compliance with regulatory and internal standards is another area machine learning is contributing to improving endpoint security. In regulated industries, including financial services, insurance, and healthcare, machine learning is being deployed to discover, classify, and protect sensitive data. This is especially the case with HIPAA (Health Insurance Portability and Accountability Act) compliance in healthcare. Amazon Macie is representative of the latest generation of machine learning-based cloud security services. Amazon Macie recognizes sensitive data such as personally identifiable information (PII) or intellectual property and provides organizations with dashboards, alerts, and contextual insights that give visibility into how data is being accessed or moved. The fully managed service continuously monitors data access activity for anomalies and generates detailed alerts when it detects the risk of unauthorized access or inadvertent data leaks. An example of one of Amazon Macie’s dashboard is shown below:

Three Reasons Why Killing Passwords Improves Your Cloud Security

Jack Dorsey’s Twitter account getting hacked by having his telephone number transferred to another account without his knowledge is a wake-up call to everyone of how vulnerable mobile devices are. The hackers relied on SIM swapping and convincing Dorsey’s telecom provider to bypass requiring a passcode to modify his account. With the telephone number transferred, the hackers accessed the Twitter founder’s account. If the telecom provider had adopted zero trust at the customer’s mobile device level, the hack would have never happened.

Cloud Security’s Weakest Link Is Mobile Device Passwords

The Twitter CEO’s account getting hacked is the latest in a series of incidents that reflect how easy it is for hackers to gain access to cloud-based enterprise networks using mobile devices. Verizon’s Mobile Security Index 2019 revealed that the majority of enterprises, 67%, are the least confident in the security of their mobile assets than any other device. Mobile devices are one of the most porous threat surfaces a business has. They’re also the fastest-growing threat surface, as every employee now relies on their smartphones as their ID. IDG’s recent survey completed in collaboration with MobileIron, titled Say Goodbye to Passwords found that 89% of security leaders believe that mobile devices will soon serve as your digital ID to access enterprise services and data.

Because they’re porous, proliferating and turning into primary forms of digital IDs, mobile devices and their passwords are a favorite onramp for hackers wanting access to companies’ systems and data in the cloud. It’s time to kill passwords and shut down the many breach attempts aimed at cloud platforms and the valuable data they contain.

Three Reasons Why Killing Passwords Improves Your Cloud Security

Killing passwords improve cloud security by:

  1. Eliminating privileged access credential abuse. Privileged access credentials are best sellers on the Dark Web, where hackers bid for credentials to the world’s leading banking, credit card, and financial management systems. Forrester estimates that 80% of data breaches involve compromised privileged credentials, and a recent survey by Centrify found that 74% of all breaches involved privileged access abuse. Killing passwords shuts down the most common technique hackers use to access cloud systems.
  2. Eliminating the threat of unauthorized mobile devices accessing business cloud services and exfiltrating data. Acquiring privileged access credentials and launching breach attempts from mobile devices is the most common hacker strategy today. By killing passwords and replacing them with a zero-trust framework, breach attempts launched from any mobile device using pirated privileged access credentials can be thwarted. Leaders in the area of mobile-centric zero trust security include MobileIron, whose innovative approach to zero sign-on solves the problems of passwords at scale. When every mobile device is secured through a zero-trust platform built on a foundation of unified endpoint management (UEM) capabilities, zero sign-on from managed and unmanaged services become achievable for the first time.
  3. Giving organizations the freedom to take a least-privilege approach to grant access to their most valuable cloud applications and platforms. Identities are the new security perimeter, and mobile devices are their fastest-growing threat surface. Long-standing traditional approaches to network security, including “trust but verify” have proven ineffective in stopping breaches. They’ve also shown a lack of scale when it comes to protecting a perimeter-less enterprise. What’s needed is a zero-trust network that validates each mobile device, establishes user context, checks app authorization, verifies the network, and detects and remediates threats before granting secure access to any device or user. If Jack Dorsey’s telecom provider had this in place, his and thousands of other people’s telephone numbers would be safe today.

Conclusion

The sooner organizations move away from being so dependent on passwords, the better. The three reasons why killing passwords improve cloud security are just the beginning. Imagine how much more effective distributed DevOps teams will be when security isn’t a headache for them anymore, and they can get to the cloud-based resources they need to get apps built. And with more organizations adopting a mobile-first development strategy, it makes sense to have a mobile-centric zero-trust network engrained in key steps of the DevOps process. That’s the future of cloud security, starting with the DevOps teams creating the next generation of apps today.

Mobile Identity Is The New Security Perimeter

  • 86% of enterprise executives say that mobile threats are growing faster than any other according to Verizon’s Mobile Security Index 2019 and 67% of enterprise execs are less confident about the security of their mobile devices compared to other IT assets.
  • Mobile devices are hackers’ favorite platform to target, with over 905,000 malware packages installed in Q1 of this year alone and over 5.3 million in 2018, according to Statistica.
  • 38% of mobile devices introduce unnecessary risk into the organization based on an analysis of privacy and security settings according to MobileIron’s Global Threat Report.

Mobile devices reflect you and your customers’ identity in the many apps, data, and ongoing activities you and they choose to engage in. Every enterprise looking to reinvent itself by scaling digital business strategies is putting mobile devices at the center of growth plans because they are everyone’s identity.

89% of security leaders believe that mobile devices will serve as your digital ID to access enterprise services and data in the near future according to a recent survey by IDG completed in conjunction with MobileIron, titled Say Goodbye to Passwords. You can download a copy of the study here. Mobile devices are increasingly becoming the IDs enterprises rely on to create and scale a mobile-centric zero trust security network throughout their organizations.

Enterprises are relying on mobile devices more than ever before, personalizing them for each associate or employee to launch and scale new business initiatives. These factors combined are leading to a rapid expansion of, and reliance on mobile devices as the single digital ID enterprises rely on to enable perimeter-less borders. The following IDG survey results reflect enterprise security leaders’ prediction of when mobile devices will authenticate Identity Access Management (IAM):

Passwords Aren’t Strong Enough For A Zero Trust World   

The bottom line is that passwords are the weakest defense in a zero-trust world. Ineffective in stopping privileged credential-based breaches, with the most privileged system access credentials shared and at times resold by insiders, passwords give hackers a key to the front door of enterprises’ systems. They no longer have to hack their way in; stolen or purchased passwords and privileged access credentials available on the Dark Web-enable hackers to use the front door of enterprise IT.

Both the IDG study published in conjunction with MobileIronSay Goodbye to Passwords and Passwordless Authentication: Bridging the Gap Between High-Security and Low-Friction Identity Management by Enterprise Management Associates (EMA) validate how weak passwords are in a zero-trust world and the many reasons they need to go.  Here are a few of the many factors that favor move beyond passwords to mobile-centric zero-trust security framework:

  • While 95% of enterprise executives say they have multi-factor authentication (MFA) implemented, a little more than half of their users are using it. Senior security executives say they doubt the security benefits (36%), expense (33%), and the decision that users don’t access sensitive information (45%), making MFA pointless.
  • 86% of senior security executives would dump password use as an authentication method if they could. In fact, nearly half of those surveyed cited eliminating passwords as a way to cut almost half of all breach attempts. Perceived security shortcomings are a key reason why almost three-quarters of these security leaders say they’re actively looking for replacements for passwords for authentication.
  • 62% of the senior security execs reported extreme user irritation with password lockouts. The percentage of respondents who reported extreme user frustration at password lockouts rose to 67% at companies with more than 5,000 employees. Users having to call in and change their password with IT’s help is a major drain on productivity and worker’s time. Senior security executives want to abandon passwords given how high maintenance they are to support and how they drain time and productivity from any organization.   

Creating A Mobile Zero Trust Network

The new reality for any enterprise is that mobile device identities are the new security perimeter. Mobility devices ranging from smartphones to tablets are exponentially expanding the threat surfaces that enterprises need to secure and passwords aren’t scaling to do the job. Instead of just relying on a password, secure access needs to be determined by a “never trust, always verify” approach that requires verification of the device, user, apps, networks, and evaluation of the presence of threats before granting access.
The formidable challenges of securing a perimeter-less enterprise where the mobile device identities are the new security perimeter need a mobile-centric zero-trust network to succeed. Zero trust validates the device, establishes user context, checks app authorization, verifies the network, and detects and remediates threats—all before granting secure access to any device or user.  Zero trust platforms are built on unified endpoint management (UEM) systems and their enabling technologies including zero sign-on (ZSO) user and device authentication, multi-factor authentication (MFA), and mobile threat detection (MTD). The following illustration reflects best practices in provisioning, granting access, protecting, enforcing, and provisioning access privileges for a mobile Zero Trust network.

Conclusion

Your smartphone or mobile device of choice is increasingly going to become your ID and secure access to resources across the enterprises you work for. Passwords have proven to be ineffective in thwarting the most common source of breaches, which is privileged credential abuse.  Enterprise executives interviewed for two completely different studies reached the same conclusion: IT infrastructure will be much safer once passwords are gone.

Your Mobile Phone Is Your Identity. How Do You Protect It?

 The average cost of a data breach has risen 12% over the past 5 years and is now $3.92M. U.S.-based breaches average $8.19M in losses, leading all nations. Not integrating mobile phone platforms and protecting them with a Zero Trust Security framework can add up to $240K to the cost of a breach. Companies that fully deploy security automation technologies experience around half the cost of a breach ($2.65M on average) compared to those that do not deploy these technologies ($5.16M on average). These and many other fascinating insights are from the 14th annual IBM Security Cost of a Data Breach Report, 2019. IBM is making a copy of the report available here for download (76 pp., PDF, opt-in). IBM and Ponemon Institute collaborated on the report, recruiting 507 organizations that have experienced a breach in the last year and interviewing more than 3,211 individuals who are knowledgeable about the data breach incident in their organizations. A total of 16 countries and 17 industries were included in the scope of the study. For additional details regarding the methodology, please see pages 71 - 75 of the report. Key insights from the report include the following: Lost business costs are 36.2% of the total cost of an average breach, making it the single largest loss component of all. Detection and escalation costs are second at 31.1%, as it can take up to 206 days to first identify a breach after it occurs and an additional 73 days to contain the breach. IBM found the average breach lasts 279 days. Breaches take a heavy toll on the time resources of any organization as well, eating up 76% of an entire year before being discovered and contained. U.S.-based breaches average $8.19M in losses, leading all nations with the highest country average. The cost of U.S.-based breaches far outdistance all other countries and regions of the world due to the value and volume of data exfiltrated from enterprise IT systems based in North America. North American enterprises are also often the most likely to rely on mobile devices to enable greater communication and collaboration, further exposing that threat surface. The Middle East has the second-highest average breach loss of $5.97M. In contrast, Indian and Brazilian organizations had the lowest total average cost at $1.83M and $1.35M, respectively. Data breach costs increase quickly in integration-intensive corporate IT environments, especially where there is a proliferation of disconnected mobile platforms. The study found the highest contributing costs associated with a data breach are caused by third parties, compliance failures, extensive cloud migration, system complexity, and extensive IoT, mobile and OT environments. This reinforces that organizations need to adopt a Zero Trust Security (ZTS) framework to secure the multiple endpoints, apps, networks, clouds, and operating systems across perimeter-less enterprises. Mobile devices are enterprises’ fasting growing threat surfaces, making them one of the highest priorities for implementing ZTS frameworks. Companies to watch in this area include MobileIron, which has created a mobile-centric, zero-trust enterprise security framework. The framework is built on the foundation of unified endpoint management (UEM) and additional zero trust-enabling technologies, including zero sign-on (ZSO), multi-factor authentication (MFA), and mobile threat detection (MTD). This approach to securing access and protect data across the perimeter-less enterprise is helping to alleviate the high cost of data breaches, as shown in the graphic below. Accidental, inadvertent breaches from human error and system glitches are still the root cause for nearly half (49%) of the data breaches. And phishing attacks on mobile devices that are lost, stolen or comprised in workplaces are a leading cause of breaches due to human error. While less expensive than malicious attacks, which cost an average of $4.45M, system glitches and human error still result in costly breaches, with an average loss of $3.24M and $3.5M respectively. To establish complete control over data, wherever it lives, organizations need to adopt Zero Trust Security (ZTS) frameworks that are determined by “never trust, always verify.”. For example, MobileIron’s mobile-centric zero-trust approach validates the device, establishes user context, checks app authorization, verifies the network, and detects and remediates threats before granting secure access to a device or user. This zero-trust security framework is designed to stop accidental, inadvertent and maliciously-driven, intentional breaches. The following graphic compares the total cost for three data breach root causes: Conclusion Lost business is the single largest cost component of any breach, and it takes years to fully recover from one. IBM found that 67% of the costs of a breach accrue in the first year, 22% accrue in the second year and 11% in the third. The more regulated a company’s business, the longer a breach will accrue costs and impact operations. Compounding this is the need for a more Zero Trust-based approach to securing every endpoint across an organization. Not integrating mobile phone platforms and protecting them with a Zero Trust Security (ZTS) framework can add up to $240K to the cost of a breach. Companies working to bridge the gap between the need for securing mobile devices with ZTS frameworks include MobileIron, which has created a mobile-centric, zero-trust enterprise security framework. There’s a significant amount of innovation happening with Identity Access Management that thwarts privileged account abuse, which is the leading cause of breaches today. Centrify’s most recent survey, Privileged Access Management in the Modern Threatscape, found that 74% of all breaches involved access to a privileged account. Privileged access credentials are hackers’ most popular technique for initiating a breach to exfiltrate valuable data from enterprise systems and sell it on the Dark Web.

  • The average cost of a data breach has risen 12% over the past 5 years and is now $3.92M.
  • U.S.-based breaches average $8.19M in losses, leading all nations.
  • Not integrating mobile phone platforms and protecting them with a Zero Trust Security framework can add up to $240K to the cost of a breach.
  • Companies that fully deploy security automation technologies experience around half the cost of a breach ($2.65M on average) compared to those that do not deploy these technologies ($5.16M on average).

These and many other fascinating insights are from the 14th annual IBM Security Cost of a Data Breach Report, 2019. IBM is making a copy of the report available here for download (76 pp., PDF, opt-in). IBM and Ponemon Institute collaborated on the report, recruiting 507 organizations that have experienced a breach in the last year and interviewing more than 3,211 individuals who are knowledgeable about the data breach incident in their organizations. A total of 16 countries and 17 industries were included in the scope of the study. For additional details regarding the methodology, please see pages 71 – 75 of the report.

Key insights from the report include the following:

  • Lost business costs are 36.2% of the total cost of an average breach, making it the single largest loss component of all. Detection and escalation costs are second at 31.1%, as it can take up to 206 days to first identify a breach after it occurs and an additional 73 days to contain the breach. IBM found the average breach lasts 279 days. Breaches take a heavy toll on the time resources of any organization as well, eating up 76% of an entire year before being discovered and contained.

  • U.S.-based breaches average $8.19M in losses, leading all nations with the highest country average. The cost of U.S.-based breaches far outdistance all other countries and regions of the world due to the value and volume of data exfiltrated from enterprise IT systems based in North America. North American enterprises are also often the most likely to rely on mobile devices to enable greater communication and collaboration, further exposing that threat surface. The Middle East has the second-highest average breach loss of $5.97M. In contrast, Indian and Brazilian organizations had the lowest total average cost at $1.83M and $1.35M, respectively.

  • Data breach costs increase quickly in integration-intensive corporate IT environments, especially where there is a proliferation of disconnected mobile platforms. The study found the highest contributing costs associated with a data breach are caused by third parties, compliance failures, extensive cloud migration, system complexity, and extensive IoT, mobile and OT environments. This reinforces that organizations need to adopt a Zero Trust Security (ZTS) framework to secure the multiple endpoints, apps, networks, clouds, and operating systems across perimeter-less enterprises. Mobile devices are enterprises’ fasting growing threat surfaces, making them one of the highest priorities for implementing ZTS frameworks. Companies to watch in this area include MobileIron, which has created a mobile-centric, zero-trust enterprise security framework. The framework is built on the foundation of unified endpoint management (UEM) and additional zero trust-enabling technologies, including zero sign-on (ZSO), multi-factor authentication (MFA), and mobile threat detection (MTD). This approach to securing access and protect data across the perimeter-less enterprise is helping to alleviate the high cost of data breaches, as shown in the graphic below.

  • Accidental, inadvertent breaches from human error and system glitches are still the root cause for nearly half (49%) of the data breaches. And phishing attacks on mobile devices that are lost, stolen or comprised in workplaces are a leading cause of breaches due to human error. While less expensive than malicious attacks, which cost an average of $4.45M, system glitches and the human error still result in costly breaches, with an average loss of $3.24M and $3.5M respectively. To establish complete control over data, wherever it lives, organizations need to adopt Zero Trust Security (ZTS) frameworks that are determined by “never trust, always verify.”. For example, MobileIron’s mobile-centric zero-trust approach validates the device, establishes user context, checks app authorization, verifies the network, and detects and remediates threats before granting secure access to a device or user. This zero-trust security framework is designed to stop accidental, inadvertent and maliciously-driven, intentional breaches. The following graphic compares the total cost for three data breach root causes:

Conclusion

Lost business is the single largest cost component of any breach, and it takes years to fully recover from one. IBM found that 67% of the costs of a breach accrue in the first year, 22% accrue in the second year and 11% in the third.  The more regulated a company’s business, the longer a breach will accrue costs and impact operations. Compounding this is the need for a more Zero Trust-based approach to securing every endpoint across an organization.

Not integrating mobile phone platforms and protecting them with a Zero Trust Security (ZTS) framework can add up to $240K to the cost of a breach. Companies working to bridge the gap between the need for securing mobile devices with ZTS frameworks include MobileIron, which has created a mobile-centric, zero-trust enterprise security framework. There’s a significant amount of innovation happening with Identity Access Management that thwarts privileged account abuse, which is the leading cause of breaches today. Centrify’s most recent survey, Privileged Access Management in the Modern Threatscape, found that 74% of all breaches involved access to a privileged account. Privileged access credentials are hackers’ most popular technique for initiating a breach to exfiltrate valuable data from enterprise systems and sell it on the Dark Web.

Why AI Is The Future Of Cybersecurity

These and many other insights are from Capgemini’s Reinventing Cybersecurity with Artificial Intelligence Report published this week. You can download the report here (28 pp., PDF, free, no opt-in). Capgemini Research Institute surveyed 850 senior executives from seven industries, including consumer products, retail, banking, insurance, automotive, utilities, and telecom. 20% of the executive respondents are CIOs, and 10% are CISOs. Enterprises headquartered in France, Germany, the UK, the US, Australia, the Netherlands, India, Italy, Spain, and Sweden are included in the report. Please see page 21 of the report for a description of the methodology.

Capgemini found that as digital businesses grow, their risk of cyberattacks exponentially increases. 21% said their organization experienced a cybersecurity breach leading to unauthorized access in 2018. Enterprises are paying a heavy price for cybersecurity breaches: 20% report losses of more than $50 million. Centrify’s most recent survey, Privileged Access Management in the Modern Threatscape, found that 74% of all breaches involved access to a privileged account. Privileged access credentials are hackers’ most popular technique for initiating a breach to exfiltrate valuable data from enterprise systems and sell it on the Dark Web.

Key insights include the following:

  • 69% of enterprises believe AI will be necessary to respond to cyberattacks. The majority of telecom companies (80%) say they are counting on AI to help identify threats and thwart attacks. Capgemini found the telecom industry has the highest reported incidence of losses exceeding $50M, making AI a priority for thwarting costly breaches in that industry. It’s understandable by Consumer Products (78%), and Banking (75%) are 2nd and 3rd given each of these industry’s growing reliance on digitally-based business models. U.S.-based enterprises are placing the highest priority on AI-based cybersecurity applications and platforms, 15% higher than the global average when measured on a country basis.

  • 73% of enterprises are testing use cases for AI for cybersecurity across their organizations today with network security leading all categories. Endpoint security the 3rd-highest priority for investing in AI-based cybersecurity solutions given the proliferation of endpoint devices, which are expected to increase to over 25B by 2021. Internet of Things (IoT) and Industrial Internet of Things (IIoT) sensors and systems they enable are exponentially increasing the number of endpoints and threat surfaces an enterprise needs to protect. The old “trust but verify” approach to enterprise security can’t keep up with the pace and scale of threatscape growth today. Identities are the new security perimeter, and they require a Zero Trust Security framework to be secure. Be sure to follow Chase Cunningham of Forrester, Principal Analyst, and the leading authority on Zero Trust Security to keep current on this rapidly changing area. You can find his blog here.

  • 51% of executives are making extensive AI for cyber threat detection, outpacing prediction, and response by a wide margin. Enterprise executives are concentrating their budgets and time on detecting cyber threats using AI above predicting and responding. As enterprises mature in their use and adoption of AI as part of their cybersecurity efforts, prediction and response will correspondingly increase. “AI tools are also getting better at drawing on data sets of wildly different types, allowing the “bigger picture” to be put together from, say, static configuration data, historic local logs, global threat landscapes, and contemporaneous event streams,” said Nicko van Someren, Chief Technology Officer at Absolute Software.

  • 64% say that AI lowers the cost to detect and respond to breaches and reduces the overall time taken to detect threats and breaches up to 12%. The reduction in cost for a majority of enterprises ranges from 1% – 15% (with an average of 12%). With AI, the overall time taken to detect threats and breaches is reduced by up to 12%. Dwell time – the amount of time threat actors remain undetected – drops by 11% with the use of AI. This time reduction is achieved by continuously scanning for known or unknown anomalies that show threat patterns. PetSmart, a US-based specialty retailer, was able to save up to $12M by using AI in fraud detection from Kount. By partnering with Kount, PetSmart was able to implement an AI/Machine Learning technology that aggregates millions of transactions and their outcomes. The technology determines the legitimacy of each transaction by comparing it against all other transactions received. As fraudulent orders were identified, they were canceled, saving the company money and avoiding damage to the brand. The top 9 ways Artificial Intelligence prevents fraud provides insights into how Kount’s approach to unsupervised and supervised machine learning stops fraud.

  • Fraud detection, malware detection, intrusion detection, scoring risk in a network, and user/machine behavioral analysis are the five highest AI use cases for improving cybersecurity. Capgemini analyzed 20 use cases across information technology (IT), operational technology (OT) and the Internet of Things (IoT) and ranked them according to their implementation complexity and resultant benefits (in terms of time reduction). Based on their analysis, we recommend a shortlist of five high-potential use cases that have low complexity and high benefits. 54% of enterprises have already implemented five high impact cases. The following graphic compares the recommended use cases by the level of benefit and relative complexity.

  • 56% of senior execs say their cybersecurity analysts are overwhelmed and close to a quarter (23%) are not able to successfully investigate all identified incidents. Capgemini found that hacking organizations are successfully using algorithms to send ‘spear phishing’ tweets (personalized tweets sent to targeted users to trick them into sharing sensitive information). AI can send the tweets six times faster than a human and with twice the success. “It’s no surprise that Capgemini’s data shows that security analysts are overwhelmed. The cybersecurity skills shortage has been growing for some time, and so have the number and complexity of attacks; using machine learning to augment the few available skilled people can help ease this. What’s exciting about the state of the industry right now is that recent advances in Machine Learning methods are poised to make their way into deployable products,” said Nicko van Someren, Chief Technology Officer at Absolute Software.

Conclusion

AI and machine learning are redefining every aspect of cybersecurity today. From improving organizations’ ability to anticipate and thwart breaches, protecting the proliferating number of threat surfaces with Zero Trust Security frameworks to making passwords obsolete, AI and machine learning are essential to securing the perimeters of any business.  One of the most vulnerable and fastest-growing threat surfaces are mobile phones. The two recent research reports from MobileIronSay Goodbye to Passwords (4 pp., PDF, opt-in) in collaboration with IDG, and Passwordless Authentication: Bridging the Gap Between High-Security and Low-Friction Identity Management (34 pp., PDF, opt-in) by Enterprise Management Associates (EMA) provide fascinating insights into the passwordless future. They reflect and quantify how ready enterprises are to abandon passwords for more proven authentication techniques including biometrics and mobile-centric Zero Trust Security platform.

Passwords Are The Weakest Defense In A Zero Trust World

  • 90% of security professionals have witnessed security incidents stemming from the theft of credentials, according to a recent MobileIron study conducted by IDG.
  • 86% of CIO, CISO and Security VPs would abandon password authentication if they could.
  • Another survey by EMA found that mobile devices secured by biometric authentication methods present the best option for replacing passwords.
  • There is a direct correlation between the number of times a user authenticates and the number of user access problems that need to be addressed.

These and many other fascinating insights make it clear that passwords are now the weakest defense anyone can rely on in a Zero Trust world. Two recent research studies quantify just how weak and incomplete an IT security strategy based on passwords is, especially when the need to access mobile apps is proliferating. Combined, these two MobileIron reports pack a one-two punch at passwords, and how they’re not strong enough alone to protect mobile devices, the fastest proliferating threat surface in a Zero Trust world.

The first, Say Goodbye to Passwords (4 pp., PDF, opt-in) by IDG, is based on interviews with 200 IT security leaders in the US, UK, Australia, and New Zealand working in a range of industries at companies with at least 500 employees. The survey’s goal is to uncover and quantify the major authentication pain points facing enterprises.  The second, Passwordless Authentication: Bridging the Gap Between High-Security and Low-Friction Identity Management (34 pp., PDF, opt-in) by Enterprise Management Associates (EMA), is based on interviews with 200 North American-based IT professionals who are knowledgeable about their organization’s use of identity and access management services. Please see page 4 of the study for additional details regarding the methodology.

The two studies provide insights into the perils of passwords and the merits of mobile when it comes to enterprise security, user experiences, and workforce productivity:

  • 90% of respondents to the EMA survey have experienced significant password policy violations in just the last year. The most frequently reported was that identical passwords are being used to support multiple accounts (39.06%). The following graphic from the EMA study reflects password management worst practices that put an organization at a high risk of a breach. A recent survey by Centrify found that 74% of all breaches involved access to a privileged account. Hackers aren’t breaking into systems; they’re obtaining privileged access credentials and walking in the front door as the graphic below shows.

  • 88% of global security leaders believe that mobile devices will soon serve as a digital ID for accessing enterprise apps and data. In the US, the percentage rises to 91%. With cyberattacks on the rise and the disadvantages of passwords and Multi-Factor Authentication (MFA) apparent to security leaders—from both a user and a security standpoint— it’s clear that new authentication methods are needed. Hardware tokens, seen by many security leaders as a more secure option for authentication than passwords, take a hit on user-friendliness compared to biometrics on a mobile device according to the survey’s results. Among the security leaders, 72% see biometrics as more user-friendly than passwords, versus just 58% favoring tokens over passwords for ease of use.

  • Four of the top five authentication technologies IT leaders prefer over passwords are biometrics-based. What’s encouraging from the EMA study is that the majority of IT departments are actively evaluating biometrics with 82% of respondents identifying at least one of the four basic biometric approaches as a passwordless solution.

  • 87% of enterprises anticipate an increase in users needing business app access over the next 24 months. 85% of respondents reported seeing an increase in the number of users who need to access business apps from a mobile device over the past 12 months. Mobile apps dominate enterprises’ internal software development efforts according to 91% of respondents to the IDG study.

  • Eliminating passwords reduces the friction or hassles required to gain access to apps and resources while improving organization-wide security. The paradox of how to improve productivity and increase security is solved when passwords go away. Low-friction identity management approaches improve user experiences while simultaneously enhancing security and reducing management efforts as the graphic below shows:

Conclusion

Hackers would instead find ingenious ways to steal passwords and privileged access credentials than spend time attempting to hack into an organization’s systems. Mobile devices and the apps they use are the fastest growing and most unprotected threat surface there is for businesses today, making them a high priority for hackers. Relying on passwords alone to protect mobile devices makes them the weakest defense in a Zero Trust World. Eliminating passwords for more effective authentication and security approaches that are more consistent with Zero Trust is needed now.

%d bloggers like this: