MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) says that while many 'analyst-driven solutions' rely on rules created by human experts and therefore may miss attacks which do not match established patterns, a new artificial intelligence platform changes the rules of the game. The platform, dubbed AI Squared (AI2), is able to detect 85 percent of attacks -- roughly three times better than current benchmarks -- and also reduces the number of false positives by a factor of five, according to MIT. The latter is important as when anomaly detection triggers false positives, this can lead to lessened trust in protective systems and also wastes the time of IT experts which need to investigate the matter. AI2 was tested using 3.6 billion log lines generated by over 20 million users in a period of three months. The AI trawled through this information and used machine learning to cluster data together to find suspicious activity. Anything which flagged up as unusual was then presented to a human operator and feedback was issued.
