New AI security system cleverly combines machine learning and human intuition

MIT researchers have announced that they've concocted a new artificial intelligence system capable of successfully detecting 85% of cyber-attacks. The AI2 platform, produced by the MIT's Computer Science and Artificial Intelligence Laboratory (in conjunction with PatternEx, a machine learning startup), has notched up a much better record than previous systems. The 85% accuracy rating is three times better than previous benchmarks which have been recorded, and it also produced far less false positives, in fact a reduction of a factor of five was observed. MIT notes that AI2's initial testing ran over a period of three months and involved combing through some 3.6 billion log lines looking for suspicious activity, using machine learning to make the initial detections and then putting those in front of a human security analyst who confirmed whether or not a detection was an actual cyber-attack. AI2 then learned from that feedback, improving its routines for the next round of detection. Essentially, the system utilises the best in artificial intelligence smarts combined with human error correction which feeds the machine learning process, and AI2 is apparently capable of honing itself rapidly indeed.