An Artificial Immune Based Approach for Detection and Isolation Misbehavior Attacks in Wireless Networks
This addresses security vulnerabilities in wireless networks for applications like military or disaster recovery, but it is incremental as it builds on existing DSR routing protocols.
The paper tackled the problem of black hole attacks in Mobile Ad-hoc Networks (MANETs) by proposing AIS-DSR, an Artificial Immune System-based approach to detect and isolate malicious nodes, with results showing improved throughput, reduced delay, and lower packet loss compared to existing solutions.
MANETs (Mobile Ad-hoc Networks) is a temporal network, which is managed by autonomous nodes, which have the ability to communicate with each other without having fixed network infrastructure or any central base station. Due to some reasons such as dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and loss of specific offensive lines, this type of networks is not supportive against malicious nodes attacks. One of these attacks is black hole attack. In this attack, the malicious nodes absorb data packets and destroy them. Thus, it is essential to present an algorithm against the black hole attacks. This paper proposed a new approach, which improvement the security of DSR routing protocol to encounter the black hole attacks. This schema tries to identify malicious nodes according to nodes behaviors in a MANETs and isolate them from routing. The proposed protocol, called AIS-DSR (Artificial Immune System DSR) employ AIS (Artificial Immune System) to defend against black hole attacks. AIS-DSR is evaluated through extensive simulations in the ns-2 environment. The results show that AIS-DSR outperforms other existing solutions in terms of throughput, end-to-end delay, packets loss ratio and packets drop ratio.