Sinkhole Attack Detection by Enhanced Reputation-Based Intrusion Detection System

• Published in: IEEE access Vol. 12; p. 1
• Main Authors: Mohammed, Fadwa Abdul-Bari, Mekky, Nagham, Suleiman, Hassan, Hikal, Noha
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: ABC optimization technique; Intrusion detection; Intrusion detection systems; Linear programming; Optimization; Optimization techniques; Reputation-Based IDS; Routing; Routing protocols; Security; Sinkhole Attack; Sinkholes; Swarm intelligence; Wireless sensor networks; WSN
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3416270

Wireless sensor networks (WSNs) currently play an important role due to their variety of applications in several fields. Improving the overall WSN performance and avoiding its limitations and challenges have become the subject of many researchers. One of the main critical issues is transmitted data security. A sinkhole attack is one of the most dangerous attacks that can be used as a platform for starting several attacks. It has a direct influence on network performance in terms of information confidentiality, integrity, and even availability. An effective method to detect such an attack leads to improving the overall WSN performance as well as enhancing the sent data secrecy. This article introduces an enhanced intrusion detection system (IDS) to protect WSNs from sinkhole attacks. The IDS is modified with a reputation-based mechanism to make it compatible with WSN requirements. An artificial bee colony (ABC) optimization technique is implemented to improve the IDS performance. Noisy channels are added to take into consideration the nature of the WSN. The proposed system achieves more than 97% overall accuracy and a detection rate of 98% with a false positive rate of less than 1.7%, which seems superior to the results of previous works.