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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Leakage Extraction Methodologies from On-Device and Remote Side-Channels
Committee:
Dr. Mukhopahyay, Advisor
Dr. Yu, Chair
Dr. Chatterjee
Abstract: The objective of the proposed research is to develop signal processing and machine learning (ML) techniques to extract information leakage from external power, electromagnetic emissions, and on-device power side-channels. We demonstrate the following side-channel attack and defense methodologies. An improved Correlation Frequency Analysis (CFA) attack with narrow band pass filtering and windowed FFT successfully recovers encryption key on unrolled implementations of lightweight block cipher, SIMON. An EM side-channel based defense using spectral features and ML based detection to identify malware applications from benign and detect unknown applications. A ML malware analysis framework trained on features derived from wavelet coefficients of EM side-channel traces to group detected malware into families. Apart from traditional side-channels, proposed research shows dynamic power managers in software that governs voltage, frequency states of CPU, generates unique signature for different application, and can red-flag malware applications from benign. To demonstrate unique correlation, ML models are trained on application specific features derived from DVFS states time-series. The application inference is further extended to demonstrate feasibility of a malware detector for IoT devices. The extension to proposed work would demonstrate a malware detection and analysis framework utilizing multi-channel frequency scaling data from CPU and other devices to improve security of devices through dynamic power management and study energy security trade-offs.
