"Bot vs Bot in Never-Ending Cycle of Improving Artificial intelligence"

The utilization of artificial intelligence through the implementation of machine learning is expected to defeat the attacks of malware and hackers by many in the cybersecurity field, however others believe this technology does not offer the ultimate solution. The increased implementation of machine learning technology into anti-malware products for the process of learning to detect malware, will soon ignite adversarial machine learning in which attack tools learn to evade malware detection by defenders. Hyrum Anderson presents an approach in support of bolstering machine learning defenses by probing machine learning software to discover blind spots and close them before attackers get to them. This article further discusses Anderson’s presented approach to improving machine learning and how most adversaries are predicted to adopt machine learning for their attacks.

Security Week reports "Bot vs Bot in Never-Ending Cycle of Improving Artificial intelligence"