![]() ![]() Led by Dr Shivam Bhasin, NTU senior research scientist at the Temasek Laboratories at NTU, researchers used sensors in a smartphone to model which number had been pressed by its users, based on how the phone was tilted and how much light was blocked by the thumb or fingers. The previous best phone-cracking success rate was 74 percent for the 50 most common pin numbers, but NTU's technique can be used to guess all 10,000 possible combinations of four-digit PINs. Using a combination of information gathered from six sensors found in smart phones and state-of-the-art machine learning and deep learning algorithms, the researchers succeeded in unlocking Android smart phones with a 99.5 percent accuracy with only three tries, when tackling a phone that had one of the 50 most common PIN numbers.
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