• Views January 9, 2017

Artificial intelligence (AI) made its entry into the world of information security last year and it was remarkable how this innovative technology was received by this specialized audience in Europe. Usually, information security vendors constantly propagate new threats - such as the targeted attacks, the insider threats and ransomware - hype it up, and then bring appropriate solutions to the market. This time, end-users are generating most of the hype, while vendors are being the pragmatic ones.

Artificial intelligence (AI) made its entry into the world of information security last year and it was remarkable how this innovative technology was received by this specialized audience in Europe. Usually, information security vendors constantly propagate new threats - such as the targeted attacks, the insider threats and ransomware - hype it up, and then bring appropriate solutions to the market. This time, end-users are generating most of the hype, while vendors are being the pragmatic ones.

Some end-users hope for AI systems to magically solve problems, including independently mapping whole networks, assessing risk, filling asset lists, and then defending against attacks. Others have exaggerated fears that soon they will be dealing with big-brother systems that are running amok and pushing reckless security interests in environments where businesses and peoples are being managed. The third group of end-users, who have more moderate opinions, are definitely in the minority.

On the other hand, AI providers are actually outlining a more pragmatic and narrow view of what their solutions truly offer - to help the highly vulnerable employees in the security operations centers. AI technology can be better than the human brain, but only in extremely niche applications, where AI is distinguished by its indefatigability rather than by intellectual excellence. For example, the more developed correlation engines of the security information and event management (SIEM) providers with Supervised Machine Learning and Unsupervised Machine Learning, for example, assist people in the tireless search for complex anomalies in the networks.

The vast discrepancy between the sensationalism and the more pragmatic offerings indicates, above all, how conscious end-users are about the numerous construction sites in the IT security sector that are not capable of handling a technology as advanced as AI.

AI is set to have a disruptive impact on information security - either create a glittered path out of misery or be the catalyst for the final collapse under the constant competition between attackers and defenders.

To ensure a more positive outcome, itís imperative for AI providers to put a great deal of effort to bring fascination and pragmatism together into something that might interest potential customers and not disappoint. Good stories about successful risk prevention by teams, in which people and machines work together, could be particularly effective.