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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)