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Summary of Trustworthiness Research at IU Professors Kapadia, Myers, Wang Research on Side-channel Detection & Mitigation • Side-channel detection: Sidebuster (CCS 2010) • Mitigation infrastructure for wireless channel: Demultiplexing (joint work with UNL, MSR and McGill) – Automatically decompose wi-fi traffic into multiple subflows using virtual wireless interfaces Research on Sensory Malware • Speech based malware: Soundcomber (NDSS 2011) – Trojan app uses limited permissions – Captures both speech and tone based audio – Analyzes audio for credit card numbers – Uses stealthy covert channels to communicate extracted sensitive data to the “malware master” – Basic defensive architecture to prevent attack Future Sensory Malware Projects • Potential projects for next 6 months – Video mining for sensitive video • Enemy looking through your eyes? – Activity mining with accelerometers to detect group activity patterns • Infer military activity patterns based on accelerometer? Sensor to Sensor Infection Dynamics • Vulnerability Analysis: Determine the plausibility of malware to transmit from sensor to sensor via wireless signals and create an epidemic assuming human dynamics in dense metropolitan settings. – Understand Epidemic Dynamics – Effects of infection time, initial infected nodes, metropolitan density, circadian rhythms, etc…. • Builds on work using smartphones to geolocate phones not in the sensor network. Sensor Theft & Loss Prevention • Aggregate Risk Engine Structure: – SVM or other non-linear classifier • Empirically evaluate benefits of multiple sensors in risk analysis • Determine which sensor information is most useful to aggregator. • Other Sensors – Phone call & Application use patterns • (stays within Reality Mining Data Set)