Abstract
We propose SoCurity, the first NoC counter-based hardware monitoring approach for enhancing heterogeneous SoC security. With SoCurity, we develop a fast, lightweight anomalous activity detection system leveraging semi-supervised machine learning models that require no prior attack knowledge for detecting anomalies. We demonstrate our techniques with a case study on a real SoC for a connected autonomous vehicle system and find up to 96% detection accuracy.
Original language | English (US) |
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Pages (from-to) | 105-108 |
Number of pages | 4 |
Journal | IEEE Computer Architecture Letters |
Volume | 22 |
Issue number | 2 |
DOIs | |
State | Published - Jul 1 2023 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
Keywords
- Heterogeneous SoC
- anomaly detection
- denial-of-service
- network-on-chip
- semi-supervised model