信息网络安全 ›› 2022, Vol. 22 ›› Issue (3): 1-9.doi: 10.3969/j.issn.1671-1122.2022.03.001

• 等级保护 • 上一篇    下一篇

智能电网中抗主次合谋攻击的群智频谱感知加固方案

冯景瑜1,2(), 时翌飞1,2, 王腾1,2   

  1. 1. 西安邮电大学无线网络安全技术国家工程实验室,西安 710121
    2. 西安邮电大学网络空间安全学院,西安 710121
  • 收稿日期:2021-11-20 出版日期:2022-03-10 发布日期:2022-03-28
  • 通讯作者: 冯景瑜 E-mail:fengjy@xupt.edu.cn
  • 作者简介:冯景瑜(1985—),男,甘肃,副教授,博士,主要研究方向为物联网安全|时翌飞(1996—),男,陕西,硕士研究生,主要研究方向为信息系统安全|王腾(1996—),女,陕西,讲师,博士,主要研究方向为隐私保护
  • 基金资助:
    国家自然科学基金青年科学基金(62102311);国家电网有限公司科技项目(J2021206)

Crowd Spectrum Sensing Reinforcement Scheme Against Primary-secondary Collusive Attack in Smart Grid

FENG Jingyu1,2(), SHI Yifei1,2, WANG Teng1,2   

  1. 1. National Engineering Laboratory for Wireless Security, Xi’an University of Posts and Telecommunications, Xi’an 710121, China;
    2. School of Cyberspace Security, Xi’an University of Posts and Telecommunications, Xi’an 710121, China;
  • Received:2021-11-20 Online:2022-03-10 Published:2022-03-28
  • Contact: FENG Jingyu E-mail:fengjy@xupt.edu.cn

摘要:

针对智能电网中群智频谱感知易受虚假数据注入攻击的问题,文章提出一种抗主次合谋攻击的群智频谱感知加固方案。该方案首先通过主用户认证构建第一层防御加固,设计基于身份密码的签名方案防止攻击者冒充主用户,引入主用户信任值检测主次合谋发起者;然后设计MAD聚类分析算法,构建第二层防御加固,由关联主用户进行次用户信任计算,使次用户信任由单值演化为多值,形成次用户信任向量,以信任向量距离为识别依据,基于聚类分析检测主次合谋攻击实施者。实验结果表明,该方案可以提高次用户信任评估的准确性,有效降低主次合谋攻击的恶意响应数量。

关键词: 智能电网, 群智频谱感知, 信任机制, 合谋攻击

Abstract:

Spurious data injection is regarded as one of the most serious threats in the crowd spectrum sensing of smart grid. To combat such threats, this paper proposed a two-level defense reinforcement scheme against primary-secondary collusive attack. Primary user(PU) authentication was adopted to construct the first layer of defense reinforcement, in which the identity-based cryptography signature was designed to prevent attackers from impersonating a PU. Meanwhile, the trust value of PU was introduced to detect the initiator of primary-secondary collusive attack. The MAD cluster analysis algorithm was designed to realize the construction of the second layer of defense reinforcement, the secondary user(SU) trust should be calculated by different PUs. The result of SU trust evaluation was no longer a single value, but a set of individual SU trust values. For an SU, its individual trust values could compose a trust vector. By adopting the distance among trust vectors to perform cluster analysis and detect primary-secondary collusive attack conspirators, simulation results show that the two-level defense reinforcement scheme can enhance the accuracy of SU trust evaluation, and successfully reducing the malicious responses of primary-secondary collusive attack.

Key words: smart grid, crowd spectrum sensing, trust mechanism, collusive attack

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