| Title | Hardware Trojans Detection Based on BP Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Xu, Lan, Li, Jianwei, Dai, Li, Yu, Ningmei |
| Conference Name | 2020 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA) |
| Keywords | Backpropagation, BP Neural Network, composability, cyber physical security, cyber physical systems, Encryption, Hardware, hardware trojan, Neural networks, Power demand, pubcrawl, resilience, Resiliency, side channel analysis, Standards, supply chain security, trojan horse detection, Trojan horses |
| Abstract | This paper uses side channel analysis to detect hardware Trojan based on back propagation neural network. First, a power consumption collection platform is built to collect power waveforms, and the amplifier is utilized to amplify power consumption information to improve the detection accuracy. Then the small difference between the power waveforms is recognized by the back propagation neural network to achieve the purpose of detection. This method is validated on Advanced Encryption Standard circuit. Results show this method is able to identify the circuits with a Trojan occupied 0.19% of Advanced Encryption Standard circuit. And the detection accuracy rate can reach 100%. |
| DOI | 10.1109/ICTA50426.2020.9332077 |
| Citation Key | xu_hardware_2020 |
Hardware Trojans Detection Based on BP Neural Network