Artificial Immune System Based Improved Secure-Aware Wormhole Attack Detection in MANET
M. Selladevi1, T. Lathamaheswari2, S. Duraisamy3 

1M. Sella Devi, Department of Computer Science, Chikkanna Govt., Arts College, Tirupur, (Tamil Nadu), India.
2T. Lathamaheswari, Department of Computer Application, Sri Krishna College of Engineering & Technology, Coimbatore, (Tamil Nadu), India.
3S. Duraisamy, Department of Computer Science, Chikkanna Govt., Arts College, Tirupur, (Tamil Nadu), India.

Manuscript received on 21 March 2019 | Revised Manuscript received on 27 March 2019 | Manuscript published on 30 July 2019 | PP: 2834-2841 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1977078219/19©BEIESP | DOI: 10.35940/ijrte.B1977.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Typically, the most significant challenge in Mobile Adhoc Network (MANET) is detecting the wormhole attacks in the network during communication that degrades the overall network performance. Many routing protocols have been developed to detect and prevent the wormhole attacks based on the requirements of hardware, synchronization clocks, etc. To avoid those requirements, Improved Secure-aware Wormhole Attack Detection (ISWAD) technique was proposed by considering the maximum end-to-end delay and path length from source to the destination node. However, it requires more parameters to further increase the detection accuracy. Therefore in this article, an Artificial Immune System (AIS) based ISWAD is proposed to detect the wormhole attacks efficiently. Initially, a scalable and distributed scheme is applied to avoid single point failures and high mobility by using the sequential probability ratio test. In this scheme, system parameters are also considered with the maximum end-to-end delay and path length. To further improve the detection rate, these parameters are learned by the AIS to detect the wormhole attacks through the network precisely. After the wormhole links/nodes are detected, an alternative path is chosen from the routing table to transmit the data from source to the destination without any packet loss. Finally, the simulation results demonstrate that the proposed technique achieves better detection rate than the other wormhole attack detection techniques.
Index Terms: MANET, Wormhole Attack Detection, ISWAD, Scalable and Distributed Scheme, Artificial Immune System.

Scope of the Article: Bio – Science and Bio – Technology