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- W3013062941 abstract "In this paper, we focus on hardware Trojans inserted into IC (Integrated Circuit) chips during IC design. We propose a hardware Trojan detection technique which is based on the chip temperature characterization by using SOM neural network. This method can achieve a high detection rate for Trojans without gold chips. First, we use a tool called HotSpot to get the steady-state heatmap from running IC. Then, we make use of 2DPCA (Dimensional Principal Component Analysis) to extract the features of the heatmap profile and feed them into a SOM (Self Organizing Map) neural network. Finally, the SOM neural network automatically distinguishes Trojan-free chips from Trojaninfected chips. The experimental results show that our method can achieve high detection rate, with 20% chip PV (Process Variability), for all centralized Trojans which are located at different positions." @default.
- W3013062941 created "2020-04-03" @default.
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- W3013062941 date "2018-07-01" @default.
- W3013062941 modified "2023-09-24" @default.
- W3013062941 title "Hardware Trojan Detection Technique Based on SOM Neural Network" @default.
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- W3013062941 doi "https://doi.org/10.1109/imccc.2018.00339" @default.
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