The basic challenge of cybersecurity is seeing enough of what is going on to determine when things are happening that shouldn't. This means detecting anomalies in the logs of system and network events that stream from every piece of an infrastructure, as well as all the major application and cloud services and environments. AI tools, without feeling bored or exhausted, can pay unwavering attention to event data streams, correlate and learn from events or observations in other environments via threat feeds. This makes AI central to the most important kind of security analysis: behavioral threat analytics (BTA). BTA, sometimes called user and entity behavioral analytics or UEBA, looks at the event streams with a focus on individual actors.

Cyberattacks have increased on an unprecedented scale. The main reason obviously is our increasing dependence on computing devices (computers, smartphones etc) and the internet for our day-to-day needs. The technology that we depend on today has interconnectedness as one of its salient features. This, plus our habit of using unsecured networks and devices (like, for example, public Wi-Fi) for convenience's sake, too has proven to be the cause for an unprecedented increase in cyberattacks. Of the various technologies that we use today to prevent cyberattacks and to ensure cybersecurity, machine learning deserves special mention.