Improved Route Discovery Scheme under Blackhole Attack in MANET

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Priyanka Pandey 1,* Raghuraj Singh 1

1. Department of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur, India

* Corresponding author.


Received: 7 Jan. 2024 / Revised: 12 Feb. 2024 / Accepted: 14 Mar. 2024 / Published: 8 Jun. 2024

Index Terms

MANET, Blackhole Attack, Routing, Security, AODV, Blackhole Detection


A Mobile Ad Hoc Network (MANET) consists of numerous wireless mobile devices. It is a self-organizing network and does not require any pre-established infrastructure. Communication between devices sets up without any dedicated centralized server. A malicious node takes advantage of this vulnerability and attempts to integrate into the network in order to lower its overall performance. In MANET, one of the most dangerous types of attacks is the blackhole node assault. In order to join the route, a node with blackhole assault wrongly sends route information to the source node during the route discovery process and degrades the network performance. In order to address this problem, a novel Blackhole Detection Algorithm (BHDA) has been proposed in this work. To determine the existence of blackhole nodes, the protocol takes into account various factors including number of route request packets (RREQ) received, number of RREQ packets forwarded, and number of route reply packets (RREP) transmitted by nodes throughout the route discovery process. Apart from this, each node maintains a local neighbourhood information and for that all neighbourhood node has to pass the check before becoming a neighbour. The simulation results prove that the proposed technique BHDA shows drastic improvement in network performance under blackhole attack.

Cite This Paper

Priyanka Pandey, Raghuraj Singh, "Improved Route Discovery Scheme under Blackhole Attack in MANET", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.14, No.3, pp. 50-60, 2024. DOI:10.5815/ijwmt.2024.03.04


[1]Loo, J., Lloret Mauri, J., & Hamilton Ortiz, J. (2011). Mobile ad hoc networks: current status and future trends.
[2]Perkins, C., Belding-Royer, E., & Das, S. (2003). RFC3561: Ad hoc on-demand distance vector (AODV) routing.
[3]Johnson, D. B., Maltz, D. A., & Broch, J. (2001). DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks. Ad hoc networking, 5(1), 139-172.
[4]Clausen, T., & Jacquet, P. (Eds.). (2003). RFC3626: Optimized link state routing protocol (OLSR). 
[5]Perkins, C. E., & Bhagwat, P. (1994). Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. ACM SIGCOMM computer communication review, 24(4), 234-244.
[6]H. Moudni, M. Er-rouidi, H. Mouncif and B. El Hadadi, "Performance analysis of AODV routing protocol in MANET under the influence of routing attacks," 2016 International Conference on Electrical and Information Technologies (ICEIT), Tangiers, Morocco, 2016, pp. 536-542, doi: 10.1109/EITech.2016.7519658.
[7]Sharma, S., & Gupta, R. (2009). Simulation study of blackhole attack in the mobile ad hoc networks. Journal of Engineering Science and Technology, 4(2), 243-250.
[8]Raj, P. N., & Swadas, P. B. (2009). Dpraodv: A dyanamic learning system against blackhole attack in aodv based manet. arXiv preprint arXiv:0909.2371.
[9]Mistry, N., Jinwala, D. C., & Zaveri, M. (2010, March). Improving AODV protocol against blackhole attacks. In international multiconference of engineers and computer scientists (Vol. 2, No. 6, pp. 1-6).
[10]Talukdar, M. I., Hassan, R., Hossen, M. S., Ahmad, K., Qamar, F., \& Ahmed, A. S. (2021). Performance improvements of AODV by black hole attack detection using IDS and digital signature. Wireless Communications and Mobile Computing, 2021, 1-13.
[11]Pandey, S., & Singh, V. (2020, July). Blackhole attack detection using machine learning approach on MANET. In 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 797-802). IEEE.
[12]Rani, P., Kavita, Verma, S., Rawat, D. B., & Dash, S. (2022). Mitigation of black hole attacks using firefly and artificial neural network. Neural Computing and Applications, 34(18), 15101-15111.
[13]Kalkha, H., Satori, H., & Satori, K. (2019). Preventing black hole attack in wireless sensor network using HMM. Procedia computer science, 148, 552-561.
[14]Shrestha, S., Baidya, R., Giri, B., & Thapa, A. (2020, March). Securing blackhole attacks in MANETs using modified sequence number in AODV routing protocol. In 2020 8th International Electrical Engineering Congress (iEECON) (pp. 1-4). IEEE.
[15Abdel-Azim, M., Salah, H. E. D., & Eissa, M. E. (2018). IDS Against Black-Hole Attack for MANET. Int. J. Netw. Secur., 20(3), 585-592.
[16]Saurabh, V. K., Sharma, R., Itare, R., & Singh, U. (2017, April). Cluster-based technique for detection and prevention of black-hole attack in MANETs. In 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA) (Vol. 2, pp. 489-494). IEEE.
[17]Kancharakuntla, D., & El-Ocla, H. (2022). EBR: Routing Protocol to Detect Blackhole Attacks in Mobile Ad Hoc Networks. Electronics, 11(21), 3480.
[18]Ram, A., Kulshrestha, J., \& Gupta, V. (2021). Secure routing-based aodv to prevent network from black hole attack in manet. In Proceedings of 6th International Conference on Recent Trends in Computing: ICRTC 2020 (pp. 633-642). Springer Singapore.
[19]Talati, V., Thorat, M., Yadav, K., & Mane, R. (2021). Detection and Prevention of Blackhole Attack in MANET Network, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056,Volume(08), Issue(05)
[20]Gupta, P., Goel, P., Varshney, P., & Tyagi, N. (2019). Reliability factor based AODV protocol: Prevention of black hole attack in MANET. In Smart Innovations in Communication and Computational Sciences: Proceedings of ICSICCS-2018 (pp. 271-279). Springer Singapore.
[21]Issariyakul, T., Hossain, E., Issariyakul, T., & Hossain, E. (2009). Introduction to network simulator 2 (NS2) (pp. 1-18). Springer US.
[22]Bettstetter, C., Hartenstein, H., & Pérez-Costa, X. (2004). Stochastic properties of the random waypoint mobility model. Wireless networks, 10, 555-567.
[23]Sarkar, T. K., Ji, Z., Kim, K., Medouri, A., & Salazar-Palma, M. (2003). A survey of various propagation models for mobile communication. IEEE Antennas and propagation.