A Trust-Management-Based Intrusion Detection System for Routing Protocol Attacks in Internet of Things | ||
| IJCI. International Journal of Computers and Information | ||
| Article 6, Volume 7, Issue 1, 2020, Pages 72-89 PDF (567.53 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ijci.2020.37546.1025 | ||
| Authors | ||
| mahmoud elbaradie* 1; Ashraf yousef Elsisi2; anas abd el aziz yousef3 | ||
| 1computer science and math department faculty of science ,tanta university,tanta,egypt. | ||
| 2Faculty of Computers and Information, Menofia University, Egypt | ||
| 3computer science,facluty of information and computer ,sheben ,monifia | ||
| Abstract | ||
| Abstract— The Internet of things is a pool of on-demand and configurable resources and services that are delivered across the usage of the internet. Providing privacy and security to protect their resources is considered a very challenging issue since the distributed architecture of the cloud makes it vulnerable to the intruders. To mitigate this issue, intrusion detection system plays an important role in detecting the attacks in the network. Intrusion detection system is a software or hardware component that implements monitoring and analysis processes of the system events or network activities. Once detecting any intrusion, an alert is raised to the administrator in order to take appropriate actions against such these intrusive events. In this paper an intrusion detection system is proposed for routing protocol for lossy and low power network attacks. The objective of the proposed system is to detect a variety of routing attacks namely sinkhole, selective forward and blackhole attacks. The detection algorithm uses trust management strategies that are based on a set of trust properties each of which is used for the detection of a specific type of routing attacks. The proposed attack detection algorithm was simulated using the Contiki Cooja simulator with centralized intrusion detection system placement strategy. The evaluation results show that in the proposed algorithm was able to detect the simulated attacks with 100% true positive detection rate in some scenarios. | ||
| Keywords | ||
| Trust Management, Internet of Things; RPL Attacks; Intrusion Detection System | ||
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