MIT builds AI bot that spots '85 per cent' of hacker invasions
MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) claim they have trained a machine-learning system to detect 85 per cent of network attacks.
To reach that level, the software, dubbed AI2 [PDF], parsed billions of lines of log files, looking for behaviors that indicate either a malware infection or a human hacker trying to get into a network. If it spotted any suspicious connections or activity, it alerted a human analyst, who identified whether the software got it right or wrong.
After 3.6 billion log lines were scanned and three months of training passed, the AI2 system was able to hit 85 per cent accuracy in detecting malicious activity, we're told.
