A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN)

Ali, Mohammed Qasim (2019) A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN). Masters thesis, Universiti Tun Hussein Onn Malaysia.


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With the continuous improvement of science and technology, wireless sensor network technology has gradually been widely used, and provides great convenience for people's living, but with the continuous improvement of the degree of application, wireless sensor network security issues also enter people's field of vision. Sensor nodes can be used for continuous sensing, event recognition and event identification. 6LoWPAN plays an important role in this convergence of heterogeneous technologies, which allows sensors to transmit information using IPv6 stack. Sensors perform critical tasks and become targets of attacks. Sinkhole attack is one of the most common attacks to sensor networks, threatening the network availability by dropping data or disturbing routing paths. RPL is a standard routing protocol commonly used in sensor networks. Therefore, this research presents the works in designing and developing Secured-RPL using the eave-listening concept (overhearing) to treating sinkhole attack. The suggested mechanism method could determine transmitted packages then overhear to the received packet, meaning that the node can overhearing to the neighbor node. Furthermore, three different simulation scenarios were applied, which are the scenario without attacker nodes, scenario with attacker nodes and the scenario with attacker and security by using Cooja simulator to Measurement and analysis performance of RPL in terms of packet delivery ratio (PDR) and power consumption over different packet transmission rate. The experimental results show that the proposed recognition method can identify sinkholes attack effectively and with less storage cost under various wireless sensor networks. Where the optimization ratio of the PDR in scenario with attacker node with the security was close to the scenario with a normal node.

Item Type: Thesis (Masters)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User: Mrs. Sabarina Che Mat
Date Deposited: 05 Aug 2021 03:27
Last Modified: 05 Aug 2021 03:27
URI: http://eprints.uthm.edu.my/id/eprint/563

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