Magneto: Leveraging Magnetic Field Changes for Inferring Smartphone App Usage

Side-channel attacks, which exploit deficiencies in the implementations of theoretically secure systems, have been known to take a variety of forms on the mobile platforms. In this work, we present Magneto, a magnetic field based app classification mechanism. Magneto captures the Hall effect due to energy consumption by different components in a smartphone, and fingerprints apps based on data captured with a Hall sensor, and a phone magnetometer. We demonstrate that our mechanism can identify magnetic field changes due to varying levels of energy consumption. We further show that Magento can not only classify between apps in the same scenario, but also can tell apart scenarios when the phone is being charged (with an AC adapter, wireless charger, or powerbank) or not. We perform validation experiments with 5 different apps, and achieve ~85% accuracy with 3 Android apps, subject to 3 different charging scenarios.