Malicious Node Detection Using a Dual Threshold in Wireless Sensor Networks

被引:8
|
作者
Lim, Sung Yul [1 ]
Choi, Yoon-Hwa [1 ]
机构
[1] Hongik Univ, Dept Comp Engn, Seoul 121791, South Korea
来源
基金
新加坡国家研究基金会;
关键词
sensor networks; malicious node detection; faults; dual threshold;
D O I
10.3390/jsan2010070
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Sensor networks for various event detection applications cannot function effectively if they are vulnerable to attacks. Malicious nodes can generate incorrect readings and misleading reports in such a way that event detection accuracy and false alarm rates are unacceptably low and high, respectively. In this paper, we present a malicious node detection scheme for wireless sensor networks. Unlike others using a single threshold, the proposed scheme employs two thresholds to cope with the strong trade-off between event detection accuracy and false alarm rate, resulting in improved malicious node detection performance. In addition, each sensor node maintains the trust values of its neighboring nodes to reflect their behavior in decision-making. Computer simulation shows that the proposed scheme achieves high malicious node detection accuracy without sacrificing normal sensor nodes and outperforms the scheme using a single threshold.
引用
收藏
页码:70 / 84
页数:15
相关论文
共 50 条
  • [1] Malicious Node Detection in Wireless Sensor Networks
    Atassi, Alaa
    Sayegh, Naoum
    Elhajj, Imad
    Chehab, Ali
    Kayssi, Ayman
    [J]. 2013 IEEE 27TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA), 2013, : 456 - 461
  • [2] Malicious Node Detection in Wireless Sensor Networks Using Support Vector Machine
    Jaint, Bhavnesh
    Indu, S.
    Pandey, Neeta
    Pahwa, Khushbu
    [J]. 2019 3RD INTERNATIONAL CONFERENCE ON RECENT DEVELOPMENTS IN CONTROL, AUTOMATION & POWER ENGINEERING (RDCAPE), 2019, : 247 - 252
  • [3] Blockchain Trust Model for Malicious Node Detection in Wireless Sensor Networks
    She, Wei
    Liu, Qi
    Tian, Zhao
    Chen, Jian-Sen
    Wang, Bo
    Liu, Wei
    [J]. IEEE ACCESS, 2019, 7 : 38947 - 38956
  • [4] Fuzzy Trust Protocol for Malicious Node Detection in Wireless Sensor Networks
    V. Ram Prabha
    P. Latha
    [J]. Wireless Personal Communications, 2017, 94 : 2549 - 2559
  • [5] Fuzzy Trust Protocol for Malicious Node Detection in Wireless Sensor Networks
    Prabha, V. Ram
    Latha, P.
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2017, 94 (04) : 2549 - 2559
  • [6] Distributed detection of mobile malicious node attacks in wireless sensor networks
    Ho, Jun-Won
    Wright, Matthew
    Das, Sajal K.
    [J]. AD HOC NETWORKS, 2012, 10 (03) : 512 - 523
  • [7] Malicious Node Detection in Wireless Sensor Networks Using an Efficient Secure Data Aggregation Protocol
    Gomathi, S.
    Krishnan, C. Gopala
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2020, 113 (04) : 1775 - 1790
  • [8] Malicious Node Detection Using Minimal Event Cycle Computation Method in Wireless Sensor Networks
    Priyanka, J. Steffi Agino
    Tephillah, S.
    Balamurugan, A. M.
    [J]. 2014 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2014,
  • [9] Malicious Node Detection in Wireless Sensor Networks Using an Efficient Secure Data Aggregation Protocol
    S. Gomathi
    C. Gopala Krishnan
    [J]. Wireless Personal Communications, 2020, 113 : 1775 - 1790
  • [10] A Novel Algorithm for Improving Malicious Node Detection Effect in Wireless Sensor Networks
    Hongyu Yang
    Xugao Zhang
    Fang Cheng
    [J]. Mobile Networks and Applications, 2021, 26 : 1564 - 1573