Authors : Prajeet Sharma; Pratima Gautam

Volume/Issue : Volume 9 - 2024, Issue 6 - June

Google Scholar : https://tinyurl.com/ez7ee8p4

Scribd : https://tinyurl.com/2chc9923

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUN1551

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Ad-hoc mobile networking (MANET) is an important technology in wireless networks with mobile nodes. Where nodes are collaborate with each other in a distributed manner and to provide multiple communications between sources and destination node. In general, the basic assumption of MANET is that each node is a trusted node. However, in a real case, there are some untrusted nodes that misbehave and attack the network like a black hole and wormhole. Where black hole nodes attract all traffic, providing false information about small hop count path to destination and with very sequence number to destinations. In wormhole attack, attacker collect data packets at one place and tunnels this data packet to another place in the network. For this attacker will give false information to the source node that the attacker node has the shortest path between sender and receiver. Source node will eventually choose that path for transmission. Once the path is established, both the nodes will drop all the incoming and outgoing packets and this causes denial of service attack, using wormhole attacks in this paper, we will discuss black hole and worm hole attack and discuss the different techniques which is used to detect and prevent these two attacks by different researchers.

Keywords : MANET, Routing Protocols, Worm Hole Attack Black Hole Attack, Performance Metrics.

References :

1. Rakesh Kumar Singh, Rajesh Joshi and Mayank Singhal “Analysis of Security Threats and Vulnerabilities in Mobile Ad Hoc Network (MANET)” International Journal of Computer Applications (0975 – 8887 Volume 68– No.4, April 2013.
2. Attacks Finding and Prevention Techniques in MANET: A Survey - Advances in Wireless and Mobile Communications. ISSN 0973-6972 Volume 10, Number 5 (2017), pp. 1185-1195 © Research India Publications http://www.ripublication.com
3. Rupali Sharma, Gray-hole Attack in Mobile Ad-hoc Networks : A Survey, ISSN: 0975-9646, International Journal of Computer Science and Information Technologies, Vol. 7 (3) , 2016, 1457-1460
4. The Impact of Resource Consumption Attack on Mobile Adhoc Network Routing” - International Journal of Network Security, Vol.16, No.4, PP.399-404, July 2014- ,
5. Network Security and Types of Attacks in Network, Mohan V. Pawar1 , Anuradha J2, - “International Conference on Intelligent Computing, Communication & Convergence 2015” -, 1877-0509 © 2015.
6. Mohamed Elboukhari , Mostafa Azizi and Abdelmalek Azizi “Impact Analysis of Blackhole attack on Mobile Adhoc Network Performance” International Journal of Grid Computing & Applications (IJGCA) Vol.6,No.1/2, June 2015 DOI:10.5121/ijgca.2015.6201
7. K.S. Arathy and C.N. Sminesh, “A novel approach for detection of single and collaborative black hole attacks in MANET,” Procedia Technology, Elsevier, 25, 2016, pp. 264-271.
8. T. Noguchi, and M. Hayakawa, “Black hole Attack Prevention Method Using Multiple reps in Mobile Ad Hoc Networks,” IEEE, 2018, pp. 539-544.
9. V.K. Saurabh, R. Sharma, R. Itare, and U. Singh, “Cluster-based technique for detection and prevention of black-hole attack in manets,” International conference of Electronics, Communication and Aerospace Technology (ICECA) IEEE, April 2017, pp. 489-494
10. M.B.M. Kame, I. Alameri, and A.N. Onaizah. “STADOV: a secure and trust based approach to mitigate blackhole attack on AODV based MANET,” IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), March2017, pp.1278- 1282.
11. M. Shivare and P.K. Gautam, “Prevention of black hole attack in MANET using indexing algorithm” IJESC,7(6), 2017, pp. 12603- 12606.
12. A. Dorri, “An EDRI- based approach for detecting and eliminating cooperative black hole nodes in MANET,” Springer, 23(6), 2017, pp. 1767-1778.
13. P. Tamilselvi and C.G. Babu, “ An efficient approach to circumvent black hole nodes in manet,” Cluster Computing, Springer, 22(5), 2017, pp. 11401-11409.
14. P.R. Jasmine Jeni, Vimala Juliet, R. Parthasarathy, A. Messiah Bose. “Performance analysis of DOA and AODV routing protocols with black hole attack in MANET” Conference: Smart Structures and Systems (ICSSS), 2013 IEEE International Conference.
15. Shikha Sharma, Manish Mahajan, Security Mechanisms for Mitigating Multiple Black Hole Attack in Manets IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 11, November 2015. Www.ijiset.com ISSN 2348 – 7968.
16. Semih et al.  Active networking: one view of the past, present, and future, Ieee Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 34, No. 1, February 2004
17. Deepika Kancharakuntla and Hosam El-Ocla “EBR: Routing Protocol to Detect Blackhole Attacks in Mobile Ad Hoc Networks “Ad Hoc Networks. Electronics 2022, 11, 3480.
18. Kim, H. Kim, G. Kim, and S. Kim, “A counterattack-detection scheme in transmission time-based wormhole detection methods,” Hindawi Publ. Corporation, Int. J. Distrib. Sens. Netw., vol. 9, no. 3. P.
19. S. Upadhyay, and B. K. Chaurasia, “Detecting and avoiding wormhole attack in MANET using statistical analysis approach,” Advances in Computer Science and Information Technology. Networks and Communications, CCSIT, 84, Springer, 2012.
20. H. Chen, W. Lou, Z. Wang, J. Wu, Z. Wang, and A. Xia, “Securing DV-Hop localization against wormhole attacks in wireless sensor networks,” Pervasive Mob. Comput., vol. 16, pp. 22–35, 2015.
21. T. V. P. Sundararajan, S. M. Ramesh, R. Maheswar, and K. R. Deepak, “Biologically inspired artificial intrusion detection system for detecting wormhole attack in MANET,” Springer Science Business Media New York, Wireless Network, 2013.
22. J. Karlsson, L. S. Dooley, and G. Pulkkis, “A new MANET wormhole detection algorithm based on traversal time and hop count analysis,” Sensors, vol. 11, pp. 11122–11140, 2011.
23. J. Karlsson, L. S. Dooley, and G. Pulkkis, “Identifying time measurement tampering in the traversal time and hop count analysis (TTHCA), wormhole detection algorithm,” Sensors, vol. 13, no. 5. Pp. 6651–6668, 2013.
24. T. Giannetsos and T. Dimitriou, “LDAC: A localized and decentralized algorithm for efficiently countering wormholes in mobile wireless networks,” J. Computer Syst. Sci., vol. 80, no. 3. Pp. 618–643, 2014.
25. S. Qazi, R. Raad, Y. Mu, and W. Susilo, “Securing DSR against wormhole attacks in multirate ad hoc networks,” J. Netw. Computer Appl., vol. 36, no. 2, pp. 582–592, 2013.
26. Xia et al., Trust prediction and trust-based source routing in mobile ad hoc networks September 2013 ,Ad Hoc Networks 11(7):2096-2114 ,DOI:10.1016/j.adhoc.2012.02.009
27. M. Anand and T. Sasikala,” Efficient energy optimization in mobile ad hoc network (MANET) using better-quality AODV protocol”, springer publications, 2018.