10 Predictions How AI Will Improve Cybersecurity In 2020
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:
- 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.”
- 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.”
- 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.”
- 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.”
- 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.”
- 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.”
- 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.
- 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.
- 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.
- 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.
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