Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (7): 2455-2463.doi: 10.13229/j.cnki.jdxbgxb.20230919

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WSNs sybil attack detection strategy integrating interactive reputation and RSSR

Zhi-jun TENG1,2(),Li-bo YU2,Ming-zhe LI2,Run-sheng MIAO2,Ji-hong WANG1,2   

  1. 1.Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology,Ministry of Education,Northeast Electric Power University,Jilin 132012,China
    2.School of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China
  • Received:2023-08-31 Online:2025-07-01 Published:2025-09-12

Abstract:

In order to resist Sybil attacks in wireless sensor networks and protect data privacy, this paper proposes a Sybil attack detection strategy for wireless sensor networks integrating interactive reputation and received signal strength ratio(SD-IR&SR) in wireless sensor networks. Introducing reputation maintenance functions and anomaly correction factors in calculating node interaction reputation values to reduce the impact of historical interaction behavior on reputation values. Establish a global reputation value matrix to calculate the average global reputation value of each node, ensuring the fairness of node reputation values. Set nodes with a global reputation average lower than the reputation threshold as untrustworthy nodes, and set up monitoring nodes to use RSSR value comparison method for detection to determine whether the node is a Sybil node. The simulation results show that SD-IR&SR can effectively detect Sybil nodes in the network, in a network where witch nodes account for 50%, it can still maintain a low packet loss rate, ensure data integrity, low latency transmission, and improve the security of wireless sensor networks.

Key words: interactive reputation value, received signal strength ratio, sybil attacks, wireless sensor network, reputation value

CLC Number: 

  • TN92

Fig.1

Network structure"

Fig.2

Sybil attack in the network"

Fig.3

Using RSSR to detect Sybil nodes"

Fig.4

SD-IR&SR algorithm flowchart"

Table 1

Simulation parameters"

参 数值或范围
网络部署区域/m2100×100
网络中节点数量/个100
节点通信半径/m20
节点初始能量/J1
节点初始信誉值0.5
数据包大小/bit800
收发能耗/(nJ·bit-150
放大器能耗/[pJ·(bit·m2-110
数据包分组发送间隔/s2
链路正常丢包率0.005~0.125
Sybil节点丢包率0.2~0.8
Γ150

Fig.5

Network topology diagram"

Fig.6

Sybil nodes trust value change graph"

Fig.7

Comparison of trust values between normal nodes and Sybil nodes"

Fig.8

Impact of reputation threshold on detection rate"

Fig.9

Impact of reputation threshold on misdetection rate"

Fig.10

Sybil node detection rate"

Fig.11

Error detection rate of Sybil nodes"

Fig.12

Comparison of end-to-end latency"

Fig.13

Comparison of packet loss rates"

Fig.14

Average residual energy"

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