Researchers from Algorithm and the Stevens Insititute of Technology have developed an algorithm, the Backward PIN-sequence Inference Binghamton University, that can collect motion data from wearables and guess PINs and passwords with an 80% accuracy rate on the first try. One way to counter an attack, the researchers suggest, is for developers to insert noise data that would disrupt motion-data collection.
Researchers from Binghamton University and the Stevens Insititute of Technology have developed an algorithm, the Backward PIN-sequence Inference Algorithm, that can collect motion data from wearables and guess PINs and passwords with an 80% accuracy rate on the first try. One way to counter an attack, the researchers suggest, is for developers to insert noise data that would disrupt motion-data collection.