MIT Creates Remarkably Accurate Tool to Detect Cyber-Attacks

They continue to target computer networks and damage their infrastructure. Now, a combined team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and machine-learning startup PatternEx has developed a powerful artificial intelligence system called AI2 which works significantly better than any existing cyber-attack detection system. The system has been tested on 3.6 billion log lines or pieces of data that reveal major system activities triggered by millions of users over a period of three months. Researchers have found that new tool can detect cyber-attacks with 85% accuracy which is roughly three times better than the previous benchmark. Moreover, it reduces the number of'false positives' – an event wrongly identified as threat – by a factor of 5. Conventional security systems are either virtual machine-based or humanly operated but none of them has proven overwhelmingly successful at encountering cyber-attacks.