Power Attack of SM4 Hardware Implementation Based on SAKURA-G Board

HU Wen-jing; WANG An; WU Li-ji; XIE Xin-jun

Chinese

您当前的位置：

首页 >

文章列表页 >

Power Attack of SM4 Hardware Implementation Based on SAKURA-G Board

更新时间：2026-09-04

- Power Attack of SM4 Hardware Implementation Based on SAKURA-G Board
- Vol. 32, Issue 4, Pages: 15-20(2015)
- 作者机构：
  
  1. 1 清华大学微电子与纳电子学系,北京,100084
  2. 2 上海通用识别技术研究所,上海,201100
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015
- 稿件说明：
移动端阅览
胡文静, 王安, 乌力吉, 谢鑫君. 基于SAKURA-G实验板的SM4硬件电路能量攻击研究[J]. 微电子学与计算机, 2015, 32(4): 15-20.

HU Wen-jing, WANG An, WU Li-ji, et al. Power Attack of SM4 Hardware Implementation Based on SAKURA-G Board[J]. 2015, 32(4): 15-20.
胡文静, 王安, 乌力吉, 谢鑫君. 基于SAKURA-G实验板的SM4硬件电路能量攻击研究[J]. 微电子学与计算机, 2015, 32(4): 15-20. DOI：

HU Wen-jing, WANG An, WU Li-ji, et al. Power Attack of SM4 Hardware Implementation Based on SAKURA-G Board[J]. 2015, 32(4): 15-20. DOI：

摘要

目前

公开研究SM4能量攻击的实验中

功耗波形都采用计算机仿真、单片机软件实现等手段

这与实际中使用的SM4硬件电路实现的功耗尚有很大差别.由此分析了一种SM4算法硬件电路实现的安全性

将它的Verilog硬件电路下载到SAKURA-G开发板中

并采集其实际运行时的功耗信息.通过相关性能量分析技术对首轮S盒输入、首轮S盒输出、首轮输出寄存器多个可能泄露信息的位置进行攻击

还原了首轮子密钥.通过相同方法可以还原第2~4轮子密钥

最终推导128比特源密钥.最后分别从系统级和算法级探讨了相应的防御对策.

Abstract

Currently

in public researches about SM4 power attack

the power traces are generated by computer simulation or software implementation. However

this is different with hardware implementation which is used in actual. A research of a SM4 algorithm hardware implementation is given out

which is applied in market. we download the Verilog code to a SAKURA-G board

and collect the power traces when it actually operates. Correlation Power Analysis method is used to analyze the leakage of the input of the S-box in the first round

the output of the S-box in the first round and the output registers of the first round. We recovered the sub-key of the first round. By the same method

we can recover the sub-keys of round 2-4

and eventually get the 128-bit key.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on the design of blockchain-based AI-generated content traceability framework

A high-efficiency charge pump for ultra-low voltage boost systems

Monte carlo analysis of V-layout trench SiC neutron detector

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰