MIT’s new AI cybersecurity platform can predict 85% of attacks

Predicting cyber attacks before they happen have two conventional approaches. One uses a set of indicators specified by an expert, and the other uses machines to detect abnormal activity. The problem with these approaches is that rules are often broken by criminals, and there is just too much abnormal activity flagged, even when these are not attacks. AI² is a collaboration between MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and PatternX, a machine learning startup with a focus on information security and threat prediction. The hybrid platform combines Artificial Intelligence, with Analyst Intuition, to give AI². The system starts with three differing unsupervised machine learning approaches to identify and tag potentially suspicious activity. These are presented to a human analyst, who can confirm or deny the tagged activity as suspicious. The…


Link to Full Article: MIT’s new AI cybersecurity platform can predict 85% of attacks