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一种混合粒度奇偶校验故障注入检测方法

王沛晶 刘强

王沛晶, 刘强. 一种混合粒度奇偶校验故障注入检测方法[J]. 北京航空航天大学学报, 2019, 45(4): 821-826. doi: 10.13700/j.bh.1001-5965.2018.0464
引用本文: 王沛晶, 刘强. 一种混合粒度奇偶校验故障注入检测方法[J]. 北京航空航天大学学报, 2019, 45(4): 821-826. doi: 10.13700/j.bh.1001-5965.2018.0464
WANG Peijing, LIU Qiang. Mixed-grain parity-code-based fault detection method against fault injection[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 821-826. doi: 10.13700/j.bh.1001-5965.2018.0464(in Chinese)
Citation: WANG Peijing, LIU Qiang. Mixed-grain parity-code-based fault detection method against fault injection[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 821-826. doi: 10.13700/j.bh.1001-5965.2018.0464(in Chinese)

一种混合粒度奇偶校验故障注入检测方法

doi: 10.13700/j.bh.1001-5965.2018.0464
基金项目: 

国家自然科学基金 61574099

详细信息
    作者简介:

    王沛晶  女, 硕士研究生。主要研究方向:集成电路安全

    刘强  男, 博士, 副教授, 博士生导师。主要研究方向:大规模集成电路设计与安全

    通讯作者:

    刘强, E-mail: qiangliu@tju.edu.cn

  • 中图分类号: TN407

Mixed-grain parity-code-based fault detection method against fault injection

Funds: 

National Natural Science Foundation of China 61574099

More Information
  • 摘要:

    为了实现高效的抗故障注入攻击,提出了一种混合粒度奇偶校验故障注入检测方法。传统奇偶校验检测方法为每n比特设置一个奇偶位,表示该n比特的奇偶性。随着n的减小,奇偶位个数增加,资源消耗增加,检测率提高。为了实现故障检测率和资源消耗的折中,对电路故障注入敏感部分或关键部分处理的数据采用细粒度奇偶校验(即n值较小),对其他部分采用粗粒度奇偶校验。以RC5加密算法为例,阐述了混合粒度奇偶校验故障检测方法的原理和应用,并对不同粒度奇偶校验方法的故障检测率及资源使用进行了理论分析。实验结果表明,与整个RC5电路都采用字(n=32 bit)奇偶校验相比,混合粒度奇偶校验故障注入检测方法可以提高故障检测率29.44%,仅增加资源消耗2.48%。

     

  • 图 1  奇偶校验故障检测结构

    Figure 1.  Parity-code-based fault detection architecture

    图 2  RC5加密电路混合粒度故障检测实现

    Figure 2.  Architecture of mixed-grain fault detection for RC5 encrypted circuit

    图 3  时钟故障注入示意图

    Figure 3.  Schematic diagram of clock fault injection

    图 4  不同混合粒度检测方法寄存器消耗值

    Figure 4.  Register utilization of different mixed-grain detection methods

    图 5  不同混合粒度检测方法故障检测率

    Figure 5.  Fault coverage of different mixed-grain detection methods

    表  1  不同粒度校验方法故障检测率理论值

    Table  1.   Fault coverage in theory of multi-granularity detection methods

    不同比特奇偶校验/bit 故障检测率/%
    32 50
    16 75
    8 93.75
    4 99.60
    下载: 导出CSV

    表  2  不同粒度校验方法寄存器消耗理论值

    Table  2.   Register utilization in theory of multi-granularity detection methods

    不同比特奇偶校验/bit 寄存器数量
    预测电路 比较电路
    32 8 1
    16 16 2
    8 32 4
    4 64 8
    下载: 导出CSV

    表  3  不同粒度校验方法故障检测率实际值

    Table  3.   Fault coverage in practice of multi-granularity detection methods

    不同比特奇偶校验/bit 故障检测率/%
    32 51.92
    16 73.97
    8 89.24
    4 96.28
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-08-03
  • 录用日期:  2018-09-14
  • 网络出版日期:  2019-04-20

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