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Tremors: Privacy-Breaching Inference of Computing Tasks Using Vibration-Based Condition Monitors

We propose the adaptation of vibration-based condition monitoring systems and techniques, popularly used in industrial condition-based maintenance, for identifying the possibility of compromising the privacy of personal computing systems. This work exploits the automated fan-based heat dissipation features and read/write operations of disk-based storage, commonly present in personal computers, to read computing task-specific vibration signatures on the computer’s cabinet/case. These vibration signatures are then used to identify the broad classes of tasks being executed on a separate computer without ever needing to log into the monitored machine. This work builds upon the premise that heterogeneous tasks have distinct computing requirements, which translates to variations in the amount of heat generated by the computer’s processor, eventually leading to variations in the computer’s heat control fan speed. The variations in the fan’s speed and the frequency of read/write operations to disk-based storage create unique vibration signatures, which maps uniquely to the computer’s processing operations, leading to a breach of privacy of the computer. Our work’s preliminary results suggest that computer-based tasks can be mapped from their vibration signatures with an accuracy of at least <inline-formula><tex-math notation="LaTeX">$70\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>70</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="misra-ieq1-3139181.gif"/></alternatives></inline-formula>. We additionally study the task identification granularity of such an approach.