A Fuzzy Trust Evaluation of Cloud Collaboration Outlier Detection in Wireless Sensor Networks

被引:7
|
作者
Sabitha, R. [1 ]
Shukla, Anand Prakash [2 ]
Mehbodniya, Abolfazl [3 ]
Shakkeera, L. [4 ]
Reddy, Punduru Chandra Shaker [5 ]
机构
[1] Hindustan Coll Engn & Technol, Dept Elect & Commun Engn, Coimbatore 641050, Tamil Nadu, India
[2] KIET Grp Inst, Dept Comp Sci, Ghaziabad 201206, Delhi, India
[3] Kuwait Coll Sci & Technol KCST, Dept Elect & Commun Engn, Doha Area,7th Ring Rd, Doha, Kuwait
[4] VIT Bhopal Univ, Sch Comp Sci & Engn, Bhopal 466114, Madhya Pradesh, India
[5] CMR Coll Engn & Technol, Dept Comp Sci & Engn, Hyderabad, TS, India
关键词
WSN; cloud; fuzzy; trust evaluation; outlier detection; ROUTING ALGORITHM; ENERGY-AWARE; SECURE; PROTOCOL; INTERNET; SCHEME; MODEL;
D O I
10.32908/ahswn.v53.8447
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
One of the primary challenges in Wireless Sensor Networks (WSNs) is security. This research proposes an efficient fuzzy trust evaluation of cloud collaboration outlier detection (FTCO) in WSNs to ensure security in clustered WSNs. In the beginning, an interval type-2 fuzzy logic con-troller is used for trusts estimation in an open wireless medium to deal with transmission uncertainty. Then, to prevent fraudulent nodes from becoming cluster heads (CHs), an outlier detection based on density approach is employed to obtain an adaptive trust threshold. Furthermore, a fuzzy-based CHs election mechanism is proposed to strike a balance among security assurance and energy conservation, with a normal sensor node with greater residual energy or lower trust in various nodes having a higher possibility of being the CH. Experimental tests show that our fuzzy-based clustering technique can highly defend the network against assaults from hostile or the compromised nodes within the network and the network lifetime is found to be 40 % higher than other systems.
引用
收藏
页码:165 / 188
页数:24
相关论文
共 50 条
  • [1] A Secure Clustering Protocol With Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks
    Yang, Liu
    Lu, Yinzhi
    Yang, Simon X.
    Guo, Tan
    Liang, Zhifang
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (07) : 4837 - 4847
  • [2] An Evolutionary Game-Based Secure Clustering Protocol With Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks
    Yang, Liu
    Lu, Yinzhi
    Yang, Simon X.
    Zhong, Yuanchang
    Guo, Tan
    Liang, Zhifang
    IEEE SENSORS JOURNAL, 2021, 21 (12) : 13935 - 13947
  • [3] Outlier Detection in Wireless Sensor Networks Based on Neighbourhood
    Gupta, Umang
    Bhattacharjee, Vandana
    Bishnu, Partha Sarathi
    WIRELESS PERSONAL COMMUNICATIONS, 2021, 116 (01) : 443 - 454
  • [4] Outlier Detection in Wireless Sensor Networks Based on Neighbourhood
    Umang Gupta
    Vandana Bhattacharjee
    Partha Sarathi Bishnu
    Wireless Personal Communications, 2021, 116 : 443 - 454
  • [5] Gravitational outlier detection for wireless sensor networks
    Bharti, Sourabh
    Pattanaik, Kiran K.
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2016, 29 (13) : 2015 - 2027
  • [6] An Efficient Dynamic Trust Evaluation Model for Wireless Sensor Networks
    Ye, Zhengwang
    Wen, Tao
    Liu, Zhenyu
    Song, Xiaoying
    Fu, Chongguo
    JOURNAL OF SENSORS, 2017, 2017
  • [7] Fuzzy Trust Protocol for Malicious Node Detection in Wireless Sensor Networks
    Prabha, V. Ram
    Latha, P.
    WIRELESS PERSONAL COMMUNICATIONS, 2017, 94 (04) : 2549 - 2559
  • [8] DODS: A Distributed Outlier Detection Scheme for Wireless Sensor Networks
    Titouna, Chafiq
    Nait-Abdesselam, Farid
    Khokhar, Ashfaq
    COMPUTER NETWORKS, 2019, 161 : 93 - 101
  • [9] An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks
    Zhao, Jin
    Huang, Jifeng
    Xiong, Naixue
    IEEE ACCESS, 2019, 7 : 33859 - 33869
  • [10] In-network outlier detection in wireless sensor networks
    Joel W. Branch
    Chris Giannella
    Boleslaw Szymanski
    Ran Wolff
    Hillol Kargupta
    Knowledge and Information Systems, 2013, 34 : 23 - 54