Algorithms recommend products while we shop online or suggest songs we might like as we listen to music on streaming apps. These algorithms work by using personal information like our past purchases and browsing history to generate tailored recommendations. The sensitive nature of such data makes preserving privacy extremely important, but existing methods for solving this problem rely on heavy cryptographic tools requiring enormous amounts of computation and bandwidth. MIT researchers may have a better solution. They developed a privacy-preserving protocol that is so efficient it can run on a…
