MIT researchers analyzed a powerful cyberattack, known as a website-fingerprinting attack, and then developed strategies that dramatically reduce the attacker’s chances of success. Pictured, from left to right: graduate student Jules Drean, Mengjia Yan, the Homer A. Burnell Career Development Assistant Professor of Electrical Engineering and Computer Science, and Jack Cook ’22. Credit: Jose-Luis Olivares, MIT
Malicious agents can use machine learning to launch powerful attacks that steal information in ways that are tough to prevent and often even more difficult to study.
Attackers can capture data that “leaks” between software programs running on the same computer. They then …
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