MIT researchers use Wi-Fi signals to identify people behind walls
Snagging an unsecured Wi-Fi signal grants an inside look into their data traffic (and computer), but what if it could be used to spy on their silhouette’s throw a wall? Worse, what if it could recognize them in a crowd? MIT researchers from the Computer Science and Artificial Intelligence Lab have developed software that intercepts rebounding wireless signals see behind a wall. The technology — called RF-Capture — is accurate enough to track the motion of a human hand with reasonable accuracy and, when fed through a machine learning algorithm, can recognize people based on their unique Wi-Fi silhouette.
