Malicious modifications to printed circuit boards (PCBs) are known as hardware Trojans. These may arise when malafide third parties alter PCBs premanufacturing or postmanufacturing and are a concern in safety-critical applications, such as industrial control systems. In this research, we examine how data-driven detection can be utilized to detect such Trojans at run-time. We develop a flexible and reconfigurable PCB test bed derived from the popular open-source programmable logic controller (PLC) platform 'OpenPLC.' We then develop a Trojan detection framework, which utilizes and analyzes multimodal side channels (e.g., timing, magnetic signals, power, and hardware performance counters). We consider defender-configurable input/output (I/O) loopback test, comparison with design-document baselines, and magnetometer-aided monitoring of system behavior under defender-chosen excitations. Our approach can extend to golden-free environments. Golden (known-good) versions of the PCBs are assumed not available, but design information, datasheets, and component-level data are available. We demonstrate the efficacy of our approach on a range of Trojans instantiated in the test bed.
|Original language||English (US)|
|Number of pages||12|
|Journal||IEEE Transactions on Very Large Scale Integration (VLSI) Systems|
|State||Published - Jul 1 2022|
- Anomaly detection
- machine learning (ML)
- printed circuit board (PCB)
- timing loopback
- Trojan detection.
- Trojan horses
- Trojan detection
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Hardware and Architecture