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Malicious alterations of integrated circuits during fabrication in untrusted foundries pose major concern in terms of their reliable and trusted field operation. It is extremely difficult to discover such alterations, also referred to as "hardware Trojans" using conventional structural or functional testing strategies. In this paper, we propose a novel non-invasive, multipleparameter side-channel analysis based Trojan detection approach that is capable of detecting malicious hardware modifications in the presence of large process variation induced noise. We exploit the intrinsic relationship between dynamic current (IDDT ) and maximum operating frequency (Fmax) of a circuit to distinguish the effect of a Trojan from process induced fluctuations in IDDT . We propose a vector generation approach for IDDT measurement that can improve the Trojan detection sensitivity for arbitrary Trojan instances. Simulation results with two large circuits, a 32-bit integer execution unit (IEU) and a 128-bit Advanced Encryption System (AES) cipher, show a detection resolution of 0.04% can be achieved in presence of ±20% parameter (V th ) variations. The approach is also validated with experimental results using 120nm FPGA (Xilinx Virtex-II) chips.

Malicious modification of integrated circuits (ICs) in untrusted foundry, referred to as "Hardware Trojan", has emerged as a serious security threat. While side-channel analysis has been reported as an effective approach to detect hardware Trojans, increasing process variations in nanoscale technologies pose a major challenge, since process noise can easily mask the Trojan effect on a measured side-channel parameter, such as supply current. Besides, existing side-channel approaches suffer from reduced Trojan detection sensitivity with increasing design size. In this paper, we propose a novel scalable side-channel approach, named self-referencing, along with associated vector generation algorithm to improve the Hardware Trojan detection sensitivity under large process variations. It compares transient current signature of one region of an IC with that of another, thereby nullifying the effect of process noise by exploiting spatial correlation across regions in terms of process variations. To amplify the Trojan effect on supply current, we propose a region-based vector generation approach, which divides a circuit-undertest (CUT) into several regions and for each region, finds the test vectors which induce maximum activity in that region, while minimizing the activity in other regions. We show that the proposed side-channel approach is scalable with respect to both amount of process variations and design size. The approach is validated with both simulation and measurement results using an FPGA-based test setup for large designs including a 32-bit DLX processor core (∼ 10 5 transistors). Results shows that our approach can find ultra-small (<0.01% area) Trojans under large process variations of up to ± 20% shift in transistor threshold voltage.

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