Real-Time Hardware Based Malware and Micro-architectural Attack Detection Utilizing CMOS Reservoir Computing

Sanjeev Tannirkulam Chandrasekaran, Abraham Peedikayil Kuruvila, Kanad Basu, Arindam Sanyal

Research output: Contribution to journalArticlepeer-review

Abstract

In this work we demonstrate a novel CMOS reservoir computer (RC) prototype in 65nm CMOS that is capable of detecting Malware and micro-architectural attacks in real-time utilizing hardware performance counter (HPC) traces. A 65nm test chip achieves 96.8% and 96.5% accuracy when classifying Malware and micro-architectural attacks respectively, while achieving better classification performance than digital machine learning models and with lower energy consumption. The on-chip classifier consumes 38.2μW from a 1.2V supply while running at 40kHz.

Original languageEnglish (US)
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
DOIs
StateAccepted/In press - 2021
Externally publishedYes

Keywords

  • Hardware
  • Hardware based malware detection
  • hardware performance counters.
  • machine learning
  • Malware
  • malware
  • micro-architectural attack
  • Neurons
  • Perturbation methods
  • Program processors
  • reservoir computing
  • Reservoirs
  • Resists

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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