基于双样本KS检验的非特定TVLA方法

郑震; 严迎建; 蔡爵嵩; 刘燕江

doi:10.11959/j.issn.1000-436x.2023101

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基于双样本KS检验的非特定TVLA方法

学术论文 | 更新时间：2024-06-06

- 基于双样本KS检验的非特定TVLA方法
- Non-specific TVLA method based on two-sample KS test
- 通信学报 2023年44卷第5期页码：137-147
- 作者机构：
  
  信息工程大学密码工程学院，河南郑州 450001
- 作者简介：
  
  [ "郑震（1996- ），男，陕西宝鸡人，信息工程大学博士生，主要研究方向为侧信道安全评估技术" ]
  [ "严迎建（1973- ），男，河南扶沟人，博士，信息工程大学教授、博士生导师，主要研究方向为芯片安全技术等" ]
  [ "蔡爵嵩（1992- ），男，四川绵阳人，信息工程大学硕士生，主要研究方向为侧信道安全攻防技术" ]
  [ "刘燕江（1990- ），男，河南南阳人，博士，信息工程大学讲师，主要研究方向为芯片安全技术等" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-436x.2023101
  中图分类号： TP309
- 网络出版日期：2023-05，
  
  纸质出版日期：2023-05-25
- 稿件说明：
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郑震, 严迎建, 蔡爵嵩, 等. 基于双样本KS检验的非特定TVLA方法[J]. 通信学报, 2023,44(5):137-147.

Zhen ZHENG, Yingjian YAN, Juesong CAI, et al. Non-specific TVLA method based on two-sample KS test[J]. Journal on communications, 2023, 44(5): 137-147.
郑震, 严迎建, 蔡爵嵩, 等. 基于双样本KS检验的非特定TVLA方法[J]. 通信学报, 2023,44(5):137-147. DOI： 10.11959/j.issn.1000-436x.2023101.

Zhen ZHENG, Yingjian YAN, Juesong CAI, et al. Non-specific TVLA method based on two-sample KS test[J]. Journal on communications, 2023, 44(5): 137-147. DOI： 10.11959/j.issn.1000-436x.2023101.

摘要

测试向量泄露评估（TVLA）在能耗样本量较少时易出现“假阴性”错误。针对该问题进行了理论推导，发现对非特定TVLA，能量迹中存在泄露的采样点处得到的检验统计量t值随能耗样本量变化而变化，非泄露点处的t值则无显著变化，因此当存在泄露时不同能耗样本量下得到的t值序列的分布不同。据此提出在不同样本量下实施非特定TVLA并对得到的t值序列实施双样本KS检验以评估泄露。分别在无防护对齐仿真能耗数据、加防护对齐能耗数据集DPA Contest v4_2和加防护非对齐自测能耗数据上进行了验证，结果表明在对齐的仿真能耗数据和DPA Contest v4_2数据集上所提方法检测出泄露所需样本量较其他方法均有所减小，最多分别减小了46.1%和39.0%；在非对齐的自测能耗数据进行对齐处理后，所提方法所需能耗样本量较其他方法同样有所减小，最多减小了 29.4%。因此所提方法能够有效减小能耗样本量较小时出现“假阴性”错误的概率。

Abstract

Test vector leakage assessment (TVLA) is prone to “false negative” when the power consumption sample size is small.To address this issue

it was found that for non-specific TVLA

when the power consumption sample size changes

the test statistic t-values obtained at the leakage sampling points in the power trace vary accordingly

while the t-values at the non-leakage sampling points do not significantly vary.Therefore

when there is leakage

the distributions of the t-values obtained under different sample sizes will be different.Based on this

it was proposed to implement non-specific TVLA under different sample sizes and perform two-sample KS test on the obtained t-value sequences to evaluate whether there was leakage.Verifications were carried out based on unprotected-aligned simulation power consumption

protected-aligned power consumption dataset DPA Contest v4_2 and protected-non-aligned self-collected power consumption respectively.The results showed that the sample size required by the proposed method on the aligned simulation power consumption and DPA Contest v4_2 was reduced by at most 46.1% and 39.0% respectively.And after the alignment

the required sample size of the proposed method on the self-collected power consumption is also smaller than that of other schemes

with a maximum reduction of 29.4%.Therefore

the proposed method can effectively reduce the probability of “false negative” when the power consumption sample size is small.

关键词

Keywords

references

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