Faiq Khalid, Syed Rafay Hasan, Osman Hasan, Falah Awwad, Muhammad Shafique
Timely detection of Hardware Trojans (HT) has become a major challenge for secure integrated circuits. We present a run-time methodology for HT detection that employs a multi-parameter statistical traffic modeling of the communication channel in a given System-on-Chip (SoC). Towards this, it leverages the Hurst exponent, the standard deviation of the injection distribution and hop distribution jointly to accurately identify HT-based online anomalies. At design time, our methodology employs a property specification language to define and embed assertions in the RTL, specifying the correct communication behavior of a given SoC. At runtime, it monitors the anomalies in the communication behavior by checking the execution patterns against these assertions. We evaluate our methodology for detecting HTs in MC8051 microcontrollers. The experimental results show that with the combined analysis of multiple statistical parameters, our methodology is able to detect all the benchmark Trojans (available on trust-hub) inserted in MC8051, which directly or indirectly affect the communication-channels in SoC.