MIT Develops Machine Learning AI To Detect Cyberattacks

A new artificial intelligence platform developed by MIT and PatternEx can identify up to 85 percent of cyberattacks, according to a new research paper. Dubbed AI2, the platform is said to be significantly better at predicting cyberattacks than similar systems because it continuously incorporates new input provided by human experts. “Today’s security systems usually fall into one of two categories: man or machine,” Adam Conner-Simon from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) wrote in a post on the MIT News site.”So-called ‘analyst-driven solutions’ rely on rules created by human experts and therefore miss any attacks that don’t match the rules,” he said. “Meanwhile, today’s machine-learning approaches rely on ‘anomaly detection,’ which tends to trigger false positives that both create distrust of the system and end up having to…


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