Identifying class of previously unseen programs using RF side channels

  title={Identifying class of previously unseen programs using RF side channels},
  author={M. Chilenski and Corey Cleveland and I. Dekine and Catherine O'Donnell and G. Raz and Andrew Sciotti and L. Vertatschitsch},
  booktitle={Defense + Commercial Sensing},
We present results showing that software programs which are not part of the training set can be characterized into broad classes using involuntary RF side channels. This extends previous work on program identification through analog side channels focused on identifying the specific program out of the training set or flagging previously-unseen programs as "anomalous." This new approach enables an intrusion detection system to be robust to benign changes such as software updates and eliminates… Expand


Microsystem Identification and Fingerprinting Using RF Side Channels
  • 2
  • PDF
Radio-frequency-based anomaly detection for programmable logic controllers in the critical infrastructure
  • 27
  • PDF
Physical layer identification of embedded devices using RF-DNA fingerprinting
  • 71
  • PDF
Machine learning - a probabilistic perspective
  • K. Murphy
  • Computer Science
  • Adaptive computation and machine learning series
  • 2012
  • 5,980
  • PDF
Analytic Properties of Trackable Weak Models
  • 1
  • PDF
Observability Properties of Colored Graphs
  • 3
  • PDF
Integrated circuit with electromagnetic energy anomaly detection and processing.
  • US Patent
  • 2011