The main objective of this paper is to provide a secure-aware routing algorithm for mobile ad hoc networks. The cooperation and communication between MANET nodes are vital. This paper discusses the new algorithm which addresses the security threat in the communication networks. The proposed algorithm has three stages: 1) the Initial bait Stage; 2) Detection Stage using Reverse Tracing, And 3) Ensuring security and protection stage. The first stage is to find the existence of a malicious node on the transfer path. The Second Stage is used to find the nonmalicious node and malicious node in the transfer path. Finally, the last stage decides the malicious node in terms of the packet delivery ratio and energy value. These three stages are designed and executed using commercial software and the outputs of the proposed method are acquired. The important parameters such as Packet Loss, Misclassification rate, Detection accuracy, Packet Delivery Ratio, Throughput, and Routing Overhead is involved to discuss the performance of the proposed method. The Simulation is executed with the given parameters and final results are used to compare with the existing methods. From the comparison, it is apparent that the proposed approach has better performance than the existing methods.

Mobile ad hoc network (MANET), malicious node, black hole attack, Cooperative bait detection scheme, Packet Modification

[1] Jin-Man Kim and Jong-Wook Jang, “AODV based Energy Efficient Routing Protocol for Maximum Lifetime in MANET”, Proceedings of the Advanced International Conference on Internet and Web Applications and Services 2006.
[2] Tripti Nema et al., “Energy Efficient Adaptive Routing Algorithm in MANET with Sleep Mode”, International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970) Volume-2 Number-4 Issue-6 December-2012.
[3] Suvarna P Bhatsangave and V R Chirchi, “OAODV Routing Algorithm for Improving Energy Efficiency in MANET”, International Journal of Computer Applications 51(21):15-22, August 2012.
[4] Syed Muhammad Sajjada, Safdar Hussain Boukb, Muhammad Yousaf, “Neighbor Node Trust Based Intrusion Detection System for WSN”, Procedia Computer Science 63, pp 183 – 188,2015.
[5] Jian-Ming Chang, Po-Chun Tsou, Isaac Woungang, Han-Chieh Chao, and Chin-Feng Lai, “ Defending Against Collaborative Attacks by Malicious Nodes in MANETs: Cooperative Bait Detection Approach”, IEEE Systems Journal, Vol.9, Issue.1, 2015.
[6] Sandip Chakraborty, Sukumar Nandi, and Subhrendu Chattopadhyay, “Alleviating Hidden and Exposed Nodes in High-Throughput Wireless Mesh Networks”. IEEE Transactions on Wireless Communications, Vol.15, Issue.2, Feb 2016.
[7] Renyong Wu, Xue Deng, Rongxing Lu, and Xuemin (Sherman) Shen, “Trust-Based Anomaly Detection in Emerging Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 2015, Article ID 363569, 14 pages, 2015.
[8] W. Wang, B. Bhargava, and M. Linderman, “Defending against collaborative packet drop attacks on MANETs,” in Proc. 28th IEEE Int. Symp. Reliable Distrib. Syst., New Delhi, India, Sep. 2009.
[9] W. Kozma and L. Lazos, “REAct resource-efficient accountability for node misbehavior in ad hoc networks based on random audits,” in Proc. WiSec, pp. 103–110, 2009.
[10] S. Anandukey and M. Chawla, “Detectionofpacket dropping attack using improved acknowledgment based scheme in MANET, ”International Journal of Computer Science Issues I, Vol. 7, No. 1, pp. 12-17, 2010.
[11] H. Liu, J. G. Delgado-Frias, and S. Medidi, “Using two-timer scheme to detect selfish nodes in ad-hoc networks,” in the proceedings of International Conference Communication, Internet, and Information Technology, pp.179-184, Alberta, Canada, 2007.
[12] Pham Thi Ngoc Diep, Monika Sachdeva, “Detecting Colluding Blackhole and Greyholeattack in Delay Tolerant Networks”, ICRTEDC, Vol. 1, Special Issue. 2, 2015.
[13] JaydipSen,” Detection of Cooperative Black Hole Attack in Wireless Ad Hoc Networks”, International Journal of simulations, systems, science and technology, Vol.12, No. 4, Aug 2011.
[14] Yanzhi Ren, Mooi Choo Chuah, Jie Yang, Yingying Chen “Detecting Wormhole Attacks In Delay-Tolerant Networks” IEEE Wireless Communications, Volume 17, Issue.5, October 2010.
[15] P.Santra, “An expert forensic investigation system for detecting malicious attacks and identifying attackers in cloud environment”, International Journal of Scientific Research in Network Security and Communication, Volume 6, Issue.5, Oct 2018.
[16] Afzal Ahmad, Mohammad Asif, and Shaikh Rohan Ali, “Review paper on shallow learning and deep learning methods for network security”, International Journal of Scientific Research and Computer Science and Engineering, Volume.6, Issue.5, pp. 45-54, Oct 2018.