Attackers could be listening to what you type

Science Daily  August 14, 2019 Researchers at the Southern Methodist University investigate the capability of mobile phone sensor arrays, using audio and motion sensor data, for classifying keystrokes that occur on a keyboard in proximity to phones around a table, as would be common in a meeting. They developed a system of mixed convolutional and recurrent neural networks and deployed the system in a human subjects experiment with 20 users typing naturally while talking. Using leave-one-user-out cross validation, they found that mobile phone arrays have the ability to detect 41.8% of keystrokes and 27% of typed words correctly in such […]

Why did my classifier just mistake a turtle for a rifle?

MIT News  July 31, 2019 We know instinctively that people and machines see the world differently, but the paper showed that the difference could be isolated and measured. Researchers at MIT have shown that a computer vision model could be compromised in a so-called black-box attack by simply feeding it progressively altered images until one caused the system to fail. Recently they highlighted multiple cases in which classifiers could be duped into confusing cats and skiers for guacamole and dogs, respectively. They trained a model to identify cats based on “robust” features recognizable to humans, and “non-robust” features that humans […]