Intelligent CISO Issue 13 - Page 37

A Artificial Intelligence, Machine Learning and Deep Learning are phrases which are being referred to more and more in technology. DEREK LIN, CHIEF DATA SCIENTIST AT EXABEAM, looks past the hype and outlines the benefits of what each of these technologies have to offer. When it comes to Artificial Intelligence (AI) and Machine Learning (ML), there’s no shortage of buzz and hype. Often referred to interchangeably, Artificial Intelligence and Machine Learning are part of our daily reality and technology lexicon – whether it’s in a product marketing pitch or a Netflix recommendation for which film to see. In cybersecurity, as these and other emerging technologies like Deep Learning (DL) evolve, their capabilities FEATURE right questions and demanding to know what constitutes reality. In order to ask the right questions, let’s start with a correct understanding of the terminology. Despite all the marketing messaging, for many of us it isn’t always clear what some terms may mean. When it comes to Artificial Intelligence (AI) and Machine Learning (ML), there’s no shortage of buzz and hype. Artificial Intelligence AI is often misunderstood and not everyone agrees on its meaning. The term Artificial Intelligence first appeared in the 1950s to describe systems comprising a set of human-defined, if/ then decision rules – which have always been easily broken and hard to maintain. have become a driving force shaping modern cybersecurity solutions. At the same time, security practitioners, fatigued by the barrage of AI and ML messaging, are raising suspicions about vendor claims. At the InteropITX conference in 2018, panellists echoed the same sentiment about the hype, asking what can be legitimately claimed as AI. The audience was encouraged to look beyond the marketing spin and find out what’s really being offered. I’m glad to see the hype cycle has reached its peak. It’s a healthy sign that security practitioners are asking the www.intelligentciso.com | Issue 13 For example, static correlation rules that raise alerts – used in traditional security information and event management (SIEM) – cannot learn and adapt. This results in a high number of false positives. Such AI systems appear to be intelligent in their decision-making because they make decisions. But in reality, they’re 100% predetermined (based on static rules) and are drafted by humans. But the word ‘intelligence’ has stuck with the public since AI’s introduction. Why not? It sounds cool. Yet today AI is often little more than a catchy marketing label, liberally applied to any system that performs tasks having some semblance of automated decision-making. Deep Learning This is all the rage today. As with AI, Deep Learning evokes an air of sophistication, but it’s also subject to misunderstandings. As a tool within 37