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Malicious modification of hardware during design or fabrication has emerged as a major security concern. Such tampering (also referred to as Hardware Trojan) causes an integrated circuit (IC) to have altered functional behavior, potentially with disastrous consequences in safety-critical applications. Conventional design-time verification and post-manufacturing testing cannot be readily extended to detect hardware Trojans due to their stealthy nature, inordinately large number of possible instances and large variety in structure and operating mode. In this paper, we analyze the threat posed by hardware Trojans and the methods of deterring them. We present a Trojan taxonomy, models of Trojan operations and a review of the state-of-the-art Trojan prevention and detection techniques. Next, we discuss the major challenges associated with this security concern and future research needs to address them.Index Terms-Hardware Trojan; Design for Security; 978-1-4244-4823-4/09/$25.00 ©2009 IEEE

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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.

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