版权说明 操作指南
首页 > 成果 > 详情

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Liu, Jiahui;Li, Lang;Li, Di;Ou, Yu
通讯作者:
Li, L
作者机构:
[Ou, Yu; Liu, Jiahui; Li, Lang; Li, Di] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
[Ou, Yu; Liu, Jiahui; Li, Lang; Li, Di] Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
通讯机构:
[Li, L ] H
Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
Hengyang Normal Univ, Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
语种:
英文
关键词:
Side-channel analysis;correlation power analysis;genetic algorithm;crossover;mutation
期刊:
计算机、材料和连续体(英文)
ISSN:
1546-2218
年:
2024
卷:
79
期:
3
页码:
4641-4657
基金类别:
Hunan Provincial Natrual Science Foundation of China [2022JJ30103]; The 14th Five-Year" Key Disciplines and Application Oriented Special Disciplines of Hunan Province [351]; Science and Technology Innovation Program of Hunan Province [2016TP1020]
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
摘要:
Correlation power analysis (CPA) combined with genetic algorithms (GA) now achieves greater attack efficiency and can recover all subkeys simultaneously. However, two issues in GA-based CPA still need to be addressed: key degeneration and slow evolution within populations. These challenges significantly hinder key recovery efforts. This paper proposes a screening correlation power analysis framework combined with a genetic algorithm, named SFGA-CPA, to address these issues. SFGA-CPA introduces three operations designed to exploit CPA characteristics: propagative operation, constrained crossove...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com