A Malicious Node Detection Strategy Based on Fuzzy Trust Model and the ABC Algorithm in Wireless Sensor Network

被引：29

作者：

Pang, Baohe ^{[1
]}

Teng, Zhijun ^{[2
]}

Sun, Huiyang ^{[3
]}

Du, Chunqiu ^{[1
]}

Li, Meng ^{[1
]}

Zhu, Weihua ^{[4
]}

机构：

[1] Northeast Elect Power Univ, Sch Elect Engn, Jilin 132000, Jilin, Peoples R China

[2] Northeast Elect Power Univ, Key Lab Modern Power Syst Simulat & Control & Ren, Minist Educ, Jilin 132000, Jilin, Peoples R China

[3] Beijing Elect Sci & Technol Inst, Dept Cryptog Sci & Technol, Beijing 100000, Peoples R China

[4] Jilin Technol Coll Elect Informat, Sch Informat Technol, Jilin 132000, Jilin, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2021年 / 10卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Wireless sensor networks; Indexes; Bayes methods; Artificial intelligence; Time series analysis; Stochastic processes; Simulation; Wireless sensor network; dishonest recommendation attacks; fuzzy trust; ABC algorithm;

D O I：

10.1109/LWC.2021.3070630

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Wireless sensor network (WSN) nodes owing to their openness, are susceptible to several threats, one of which is dishonest recommendation attacks providing false trust values that favor the attacker. In this letter, a malicious node detection strategy is proposed based on a fuzzy trust model and artificial bee colony algorithm (ABC) (FTM-ABC). The fuzzy trust model (FTM) is introduced to calculate the indirect trust, and the ABC algorithm is applied to optimize the trust model for detecting dishonest recommendation attacks. Besides, fitness function includes recommended deviation and interaction index deviation to enhance the effectiveness. Simulation results reveal the improved FTM-ABC maintains a high recognition rate and a low false-positive rate, even if the number of dishonest nodes reaches 50%.

引用

页码：1613 / 1617

页数：5

共 50 条

[31] Blockchain transaction model based on malicious node detection network
Miao, Xiao-Ai
Liu, Tao
MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (14) : 41293 - 41310
[32] Blockchain transaction model based on malicious node detection network
Xiao-Ai Miao
Tao Liu
Multimedia Tools and Applications, 2024, 83 : 41293 - 41310
[33] Malicious Node Detection in Wireless Weak-Link Sensor Networks Using Dynamic Trust Management
Wang, Chenlong
Liu, Guanghua
Jiang, Tao
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2024, 23 (12) : 12866 - 12877
[34] A Routing Algorithm for Node Protection in Wireless Sensor Network Based on Clustering Ant Colony Strategy
Feng, Xiao
Wang, Yuanzheng
Dong, Tengfei
Liao, Yingxia
Zhang, Yixin
Lin, Yi
ARTIFICIAL INTELLIGENCE AND SECURITY, ICAIS 2022, PT III, 2022, 13340 : 184 - 193
[35] Fuzzy Node Localization in Wireless Sensor Network
Bhowmik, Suman
Kar, Rajib
Giri, Chandan
PROCEEDINGS OF THE 2016 IEEE INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET), 2016, : 1112 - 1116
[36] Malicious Attack Detection in Underwater Wireless Sensor Network
Ahmed, Muhammad R.
Tehsien, Syeda Manjia
Aseeri, Mohammed
Kaiser, M. Shamim
2015 IEEE INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND PHOTONICS (ICTP), 2015,
[37] Algorithm of wireless sensor network node based on the vehicle localization
Heng, Fan
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHATRONICS, ROBOTICS AND AUTOMATION (ICMRA 2015), 2015, 15 : 1420 - 1423
[38] Retraction Note: Emerging network communication for malicious node detection in wireless multimedia sensor networks
S. Arockia Jayadhas
S. Emalda Roslin
W. Florin
Optical and Quantum Electronics, 56 (10)
[39] Node Localization Algorithm Based on RSSI in Wireless Sensor Network
Wang Suzhe
Li Yong
6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS'2012), 2012,
[40] Trust-based Selfish Node Detection Mechanism using Beta Distribution in Wireless Sensor Network
Devi, Kanchana, V
Ganesan, R.
JOURNAL OF ICT RESEARCH AND APPLICATIONS, 2019, 13 (01) : 79 - 91

← 1 2 3 4 5 →