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

doi:10.3969/j.issn.1671-1122.2022.03.001

Abstract

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

CLC Number:

TP309

FENG Jingyu, SHI Yifei, WANG Teng. Crowd Spectrum Sensing Reinforcement Scheme Against Primary-secondary Collusive Attack in Smart Grid[J]. Netinfo Security, 2022, 22(3): 1-9.

Figures/Tables 6

References 23

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参数	描述	默认值
N_S	次用户数量	60
N_P	主用户数量	10
Round	攻击轮数	100
P_a	攻击者比例	30%
δ	次用户信任门限值	0.5
ε	主用户信任门限值	0.7