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Improving the Classification Accuracy in Detecting Hardware Trojan in ALU Using PCA
Present day electronic chips are outsourced by the manufacturer and done by third-parties. Such practices are widely prevalent as it works out to be more profitable in terms of cost and effort to complete these processes offshore in VLSI foundries. This comes with a potential risk of compromised security due to hardware Trojans. There are existing methodologies which aim at tacking the issue of Hardware Trojans by detecting it. Hardware Trojan detection by decomposing the design into blocks to detect combinational Trojan and Sequential Trojan is proposed in this paper. By comparing the leakage and total power values consumed by both the design i.e. with and without the presence of the hardware Trojans, we can identify the presence of the hardware Trojans. Moreover if the measurement noise gets high it masks or hides the effect of the variation in power profile, which leads to a wrong decision. So by taking the measurement noise under consideration the classification is effectively done for magnifying the differences by using Principle Component Analysis approach and tested with 8, 16 and 32 bit ALU designs.
Hardware Security, Hardware Trojan Detection, Principle Component Analysis, Side Channel Analysis.
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