Protecting mobile privacy in real time with predictive adversarial defense

Mobile sensors are everywhere, quietly recording how users move, tilt, or hold their phones. The same data that powers step counters and activity trackers can also expose personal details such as gender, age, or even identity. A new study introduces a method designed to stop that information from being inferred in the first place, without interrupting the phone’s normal functions. Overview of the PATN framework. The system includes PATN training, where the network learns to … More →

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