Power Side Channel Attack Analysis and Detection

Navyata Gattu, Mohammad Nasim Imtiaz Khan, Asmit De, Swaroop Ghosh

Research output: Contribution to journalConference articlepeer-review

12 Scopus citations


Side Channel Attack (SCA) is a serious threat to the hardware implementation of cryptographic protocols. Various side channels such as, power, timing, electromagnetic emission and acoustic noise have been explored to extract the secret keys. Machine Learning (ML)-based detection of SCA have been proposed in past which incur high design overheads and, require digitization that reduce their accuracy under process variations. We propose a real-time power SCA detection technique using on-chip sensors based on a thorough analysis. The dependency of phase/frequency of Ring Oscillator (RO) on supply voltage is exploited to detect the insertion of a SCA resistance in the power rail. The proposed approach is validated using simulation with a detailed model of Power Delivery Network (PDN) and power grid. The technique can detect a minimum resistance of 1 \Omega within 2 µs of attack initiation and incurs a tiny fraction of area/power (0.044%/0.1065%, respectively) compared to ML-based techniques.

Original languageEnglish (US)
Article number9256599
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
StatePublished - Nov 2 2020
Event39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020 - Virtual, San Diego, United States
Duration: Nov 2 2020Nov 5 2020

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design


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