基于双样本KS检验的非特定TVLA方法

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

摘要/Abstract

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。

关键词: 侧信道, 测试向量泄露评估, 假阴性, 双样本KS检验

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.

Key words: side-channel, test vector leakage assessment, false negative, two-sample KS test

中图分类号:

TP309

郑震, 严迎建, 蔡爵嵩, 刘燕江. 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, Yanjiang LIU. Non-specific TVLA method based on two-sample KS test[J]. Journal on Communications, 2023, 44(5): 137-147.

图/表 6

图1

图2

图3

图4

图5

图6

参考文献 22

[1]	KOCHER P , JAFFE J , JUN B . Differential power analysis[C]// Advances in Cryptology - CRYPTO’99. Berlin:Springer, 1999: 388-397.
[2]	BRIER E , CLAVIER C , OLIVIER F . Correlation power analysis with a leakage model[C]// Cryptographic Hardware and Embedded Systems-CHES 2004. Berlin:Springer, 2004: 16-29.
[3]	GIERLICHS B , BATINA L , TUYLS P ,et al. Mutual information analysis[C]// Cryptographic Hardware and Embedded Systems - CHES 2008. Berlin:Springer, 2008: 426-442.
[4]	吴震, 王燚, 周冠豪 . 有学习的高阶DPA攻击[J]. 通信学报, 2018,39(9): 135-146.
	WU Z , WANG Y , ZHOU G H . High order DPA with profiling[J]. Journal on Communications, 2018,39(9): 135-146.
[5]	GOODWILL G , JUN B , JAFFE J ,et al. A testing methodology for side-channel resistance validation[C]// NIST Non-Invasive Attack Testing Workshop.[S.l.:s.n.], 2011: 115-136.
[6]	STANDAERT F X . How (not) to use Welch’s t-test in side-channel security evaluations[C]// Smart Card Research and Advanced Applications. Berlin:Springer, 2019: 65-79.
[7]	DAO B A , HOANG T T , LE A T ,et al. Correlation power analysis attack resisted cryptographic RISC-V SoC with random dynamic frequency scaling countermeasure[J]. IEEE Access, 2021,9: 151993-152014.
[8]	STEINBAUER T , NAGPAL R , PRIMAS R ,et al. TVLA on selected NIST LWC finalists[EB]. 2022.
[9]	LU C C , CUI Y J , KHALID A ,et al. A novel combined correlation power analysis (CPA) attack on schoolbook polynomial multiplication in lattice-based cryptosystems[C]// Proceedings of 2022 IEEE 35th International System-on-Chip Conference (SOCC). Piscataway:IEEE Press, 2022: 1-6.
[10]	JEVTIC R , OTERO M G . Methodology for complete decorrelation of power supply EM side-channel signal and sensitive data[J]. IEEE Transactions on Circuits and Systems II:Express Briefs, 2022,69(4): 2256-2260.
[11]	DING A A , ZHANG L W , DURVAUX F ,et al. Towards sound and optimal leakage detection procedure[C]// International Conference on Smart Card Research and Advanced Applications. Berlin:Springer, 2018: 105-122.
[12]	王娅茹, 唐明 . 基于Bartlett和多分类F检验侧信道泄露评估[J]. 通信学报, 2021,42(12): 35-43.
	WANG Y R , TANG M . Side channel leakage assessment with the Bartlett and multi-classes F-test[J]. Journal on Communications, 2021,42(12): 35-43.
[13]	DING A A , CHEN C , EISENBARTH T . Simpler,faster,and more robust t-test based leakage detection[C]// International Workshop on Constructive Side-Channel Analysis and Secure Design. Berlin:Springer, 2016: 163-183.
[14]	鹿福祥, 李伟键, 黄娴 . 基于配对 t 检验的侧信道泄露评估优化研究[J]. 小型微型计算机系统, 2019,40(12): 2585-2590.
	LU F X , LI W J , HUANG X . Research on optimization of side channel leakage assessment based on paired t test[J]. Journal of Chinese Computer Systems, 2019,40(12): 2585-2590.
[15]	ZHANG L W . Statistics in side channel analysis-modeling,metric,leakage detection testing[D]. Boston:Northeastern University, 2017.
[16]	MORADI A , RICHTER B , SCHNEIDER T ,et al. Leakage detection with the x2-test[J]. IACR Transactions on Cryptographic Hardware and Embedded Systems, 2018(1): 209-237.
[17]	BACHE F , PLUMP C , GüNEYSU T . Confident leakage assessment-a side-channel evaluation framework based on confidence intervals[C]// Proceedings of 2018 Design,Automation ＆ Test in Europe Conference ＆ Exhibition (DATE). Piscataway:IEEE Press, 2018: 1117-1122.
[18]	MOOS T , WEGENER F , MORADI A . DL-LA:deep learning leakage assessment[J]. IACR Transactions on Cryptographic Hardware and Embedded Systems. 2021:doi.org/10.46586/tches.v2021.i3.552-598.
[19]	WANG Y , TANG M , WANG P ,et al. The Levene test based-leakage assessment[J]. Integration, 2022,87: 182-193.
[20]	MANGARD S , OSWALD E , POPP T . Power analysis attacks:revealing the secrets of smart cards[M]. Berlin: Springer, 2007.
[21]	BHASIN S , BRUNEAU N , DANGER J L ,et al. Analysis and Improvements of the DPA Contest v4 Implementation[C]// International Conference on Security,Privacy,and Applied Cryptography Engineering. Berlin:Springer, 2014: 201-218.
[22]	PROUFF E , RIVAIN M , BEVAN R . Statistical analysis of second order differential power analysis[J]. IEEE Transactions on Computers, 2009,58(6): 799-811.