华中科技大学学报（自然科学版）Issue(2)：51-55,5.DOI:10.13245/j.hust.160211
基于自组织竞争神经网络的硬件木马检测方法
Hardware Trojan detection technology based on self-organizing competition neural network
摘要
Abstract
Nowadays the most commonly used method for side channel hardware Trojan detection is dimensionality reduction and main feature extraction .The disadvantage is that it may lose critical in‐formation about Trojan features while selecting useful information .To solve this problem ,a Trojan detection method based on self‐organizing competition neural network was proposed .The proposed method utilized unsupervised learning ways to build mathematical models for classification and dis‐crimination between golden information and testing information .A verification system was set up based on FPGA (field‐programmable gate array ) to acquire side channel current information .Testing result shows that the proposed method can effectively detect hardware Trojan accounting an area less than 0 .16% of the golden circuit .关键词
信息技术/硬件木马检测/检测方法/侧信道分析/自组织竞争神经网络Key words
information technology/hardware Trojan detection/detection method/side channel anal-ysis/self-organizing competition neural network分类
信息技术与安全科学引用本文复制引用
赵毅强,刘沈丰,何家骥,杨松..基于自组织竞争神经网络的硬件木马检测方法[J].华中科技大学学报（自然科学版）,2016,(2):51-55,5.基金项目
国家自然科学基金资助项目（61376032）． （）
