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An Efficient Fuzzy Path Selection Approach to Mitigate Selective Forwarding Attacks in Wireless Sensor Networks
Date
2017-07-12
Author
Sert, Seyyit Alper
Fung, Carol
George, Roy
Yazıcı, Adnan
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Wireless Sensor Networks (WSNs) facilitate efficient data gathering requirements occurring in indoor and outdoor environments. A great deal of WSNs operates by sensing the area-of-interest (AOI) and transmitting the obtained data to a sink/(s). The transmitted data is then utilized in decision making processes. In this regard, security of raw and relayed data is both crucial and susceptible to malicious attempts targeting the task of the network which occurs on the wireless transmission medium. A node, when compromised, may deliberately forward data packets selectively. When this happens, nodes adjacent to the malicious nodes cannot identify the malevolent node and mitigate the effects of the attacks. In this study, we introduce a fuzzy path selection approach that efficiently mitigates single selective forwarding attacks in WSNs. Performance of our proposed approach and its evaluations are simulated and obtained. Our experimental results show that our approach is an effective solution to serve as a defense mechanism in terms of the efficiency metrics, such as Half of the Nodes Alive (HNA), Total Remaining Energy (TRE), and Packet Drop Ratio (PDR).
Subject Keywords
Fuzzy path selection
,
Selective forwarding
,
Routing security
URI
https://hdl.handle.net/11511/55251
Conference Name
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Collections
Department of Computer Engineering, Conference / Seminar
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S. A. Sert, C. Fung, R. George, and A. Yazıcı, “An Efficient Fuzzy Path Selection Approach to Mitigate Selective Forwarding Attacks in Wireless Sensor Networks,” presented at the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Naples, ITALY, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55251.