刘敏,,
邱钊洋
解放军信息工程大学 ??郑州 ??450001
详细信息
作者简介:严迎建:男,1973 年生,教授,研究方向为安全专用芯片设计技术
刘敏:女,1995年生,硕士生,研究方向为安全专用芯片设计技术硬件木马检测
邱钊洋:男,1991年生,博士生,研究方向为信号分析与软件无线电
通讯作者:刘敏 15515671017@163.com
中图分类号:TN406计量
文章访问数:1180
HTML全文浏览量:564
PDF下载量:84
被引次数:0
出版历程
收稿日期:2018-05-21
修回日期:2018-09-20
网络出版日期:2018-10-22
刊出日期:2019-05-01
Design and Implementation of Hardware Trojan Detection Algorithm for Coarse-grained Reconfigurable Arrays
Yingjian YAN,Min LIU,,
Zhaoyang QIU
The PLA’s Information Engineering University, Zhengzhou 450001, China
摘要
摘要:硬件木马检测已成为当前芯片安全领域的研究热点,现有检测算法大多面向ASIC电路和FPGA电路,且依赖于未感染硬件木马的黄金芯片,难以适应于由大规模可重构单元组成的粗粒度可重构阵列电路。因此,该文针对粗粒度可重构密码阵列的结构特点,提出基于分区和多变体逻辑指纹的硬件木马检测算法。该算法将电路划分为多个区域,采用逻辑指纹特征作为区域的标识符,通过在时空两个维度上比较分区的多变体逻辑指纹,实现了无黄金芯片的硬件木马检测和诊断。实验结果表明,所提检测算法对硬件木马检测有较高的检测成功率和较低的误判率。
关键词:硬件木马检测/
粗粒度可重构密码阵列/
逻辑指纹/
多变体
Abstract:Hardware Trojan horse detection has become a hot research topic in the field of chip security. Most existing detection algorithms are oriented to ASIC circuits and FPGA circuits, and rely on golden chips that are not infected with hardware Trojan horses, which are difficult to adapt to the coarse-grained reconfigurable array consisting of large-scale reconfigurable cells. Therefore, aiming at the structural characteristics of Coarse-grained reconfigurable cryptographic logical arrays, a hardware Trojan horse detection algorithm based on partitioned and multiple variants logic fingerprints is proposed. The algorithm divides the circuit into multiple regions, adopts the logical fingerprint feature as the identifier of the region, and realizes the hardware Trojan detection and diagnosis without golden chip by comparing the multiple variant logic fingerprints of the regions in both dimensions of space and time. Experimental results show that the proposed detection algorithm has high detection success rate and low misjudgment rate for hardware Trojan detection.
Key words:Hardware Trojan detection/
Coarse-grained reconfigurable cryptographic array/
Logic fingerprints/
Multiple variants
PDF全文下载地址:
https://jeit.ac.cn/article/exportPdf?id=3b17685d-519b-4bd9-97ec-b008868f1e67