Reliability Assessment and Detection of Nodes Causing a Blackhole Attack in Portable Informal Networks
Keywords:
Wireless, MANET, Blackhole, attack, Routing, Round trip Time, Time to live, CongestionAbstract
In mobile ad hoc networks (MANETs), the existence of malicious nodes might raise serious security issues. These nodes could interfere with the routing procedure or change the way data packets move through the network. Due to the entire framework's traits including its lack of structures, changeable topology, and central management unit, the MANET is very vulnerable to attacks. The black hole attack is one of the most frequent in MANETs, which In the event of such assaults, MANET nodes are vulnerable to a remarkable network capacity reduction. with this aspect, it is difficult with MANETs to identify or stop dishonest nodes from launching blackhole attacks. A decentralized anomaly detection system called identifying intrusions using traffic projections, which is based on this method, is created for detecting attacks that have a greater impact during packets moving, like selectively attacks with DOS or relaying strikes. Each node in TPID operates separately when anticipating volume and spotting anomalies. It is not necessary for nodes to cooperate or use specialized hardware. In experiments, the plan is assessed and contrasted with alternative methods. Results demonstrate that the suggested technique achieves a high detection efficiency with little extra cost for computation or communication. In this research, we provide an Enhanced Blackhole Resistance (EBR) mechanism to recognize and thwart blackhole attack-causing nodes. By sending the data packets through an encrypted route with the smallest RTT, EBR can avoid clogged traffic. The EBR protocol employs a TR mechanism, often known as a duration to live and time spent traveling combined, to identify blackhole assaults. No authentication or cryptographic techniques are needed for our algorithm. Compared to other protocols, EBR performs better in simulations in terms of efficiency, end-to-end delay, the delivery of packets ratio, energy use, and routing inefficiency.
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Acquisti, A.; Carrara, E.; Stutzman, F.; Callas, J.; Schimmer, K.; Nadjm, M.; Gorge, M.; Ellison, N.; King, P.; Gross, R. Security Issues and Recommendations for Online Social Networks; ENISA Position Paper No.1; ENISA—European Network and InformationSecurityAgency:Heraklion,Greece,2007;
Volume43.
Huang,K.;Zhou,C.;Tian,Y.- C.;Tu,W.;Peng,Y. Application of Bayesiannet work to data-driven cyber- security risk assessment in SCADA networks. InProceedingsofthe201727thInternationalTelecommunicationNetworksandApplicationsConference(ITNAC),Melbourne,VIC,Australia,22–24November2017;IEEE:NewYork,NY,USA,2017.
Kannan, R.; Ray, L.; Durresi, A.; Iyengar, S. Security-performance tradeoffs of inheritance based key predistribution for wireless sensor networks. arXiv2004.
Elsaeidy,A.;Elgendi,I.;Munasinghe,K.S.;Sharma,D.;Jamalipour,A.Asmartcitycybersecurityplatformfornarrowband networks .In Proceedings of the 2017 27th International Telecommunication Networks and Applications Conference (ITNAC), Melbourne, VIC, Australia, 22–24 November 2017; IEEE: New York, NY, USA, 2017.
Reddy,G .A Delay Sensitive Multi-PathSelectiontoPreventtheRushingAttackinVANET.InProceedingsofthe20215th International Conference on Information Systems and Computer Networks (ISCON), Mathura, India, 22–23 October 2021; IEEE: New York, NY, USA, 2021.
Sayan,C.;Hariri,S.;Ball,G.Cybersecurityassistant:Designoverview.InProceedingsofthe2017IEEE2ndInterna- tionalWorkshopsonFoundationsandApplicationsofSelf*Systems(FAS*W),Tucson,AZ,USA,18–22September2017; IEEE: New York, NY, USA, 2017.
Nair,R.;Ragab,M.;Mujallid,O.A.;Mohammad,K.A.;Mansour,R.F.;Viju,G.K.Impactofwirelesssensordataminingwith hybrid deep learning for human activity recognition.Wirel.Commun.Mob.Comput.2022, 2022, 9457536.
Tagarev,T.DigilienceAPlatformforDigitalTransformation,CyberSecurityandResilience.Inf.Secur.2019,43,7–10.
Hamdi,M.M.;Audah,L.;Abood,M.S.;Rashid,S.A.;Mustafa,A.S.;Mahdi,H.;Al-Hiti,A.S.Areviewonvarioussecurityattacksinvehicularadhocnetworks. Bull. Electr. Eng. Inform. 2021,10,2627–2635.
Moustafa, A.A.; Bello, A.; Maurushat, A. The role of user behaviour in improving cyber security management.Front.Psychol. 2021, 1969.
Stacey, T.R.; Helsley, R.E.; Baston, J.V. Identifying information security threats. Inf. Syst. Secur. 1996, 5, 50–59.
Sohraby, K., Minoli, D., and Znati, T.; “Wireless sensor networks: technology, protocols, and applications.” John Wiley and Sons, 2007.
Rawat, P., Singh, K. D., Chaouchi, H., and Bonnin, J. M. “Wireless sensor networks: a survey on recent developments and potential synergies.” The Journal of supercomputing, 2014, 68(1): 1–48.
Kalkha, H., Satori, H., and Satori, K.; “Performance Evaluation of AODV and LEACH Routing Protocol.” Advances in Information Technology: Theory and Application, 2016.
Nieles, M.; Dempsey, K.; Pillitteri, V. NIST Special Publication 800-12 Revision 1: An Introduction to Information Security; National Institute of Standards and Technology: Gaithersburg, MD, USA, 2017.
Zafar, F.; Khattak, H.A.; Aloqaily, M.; Hussain, R. Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions. ACM Comput. Surv. (CSUR) 2021, 54, 218.
Safaa,O.;Firas,S. On the Designing of two grains levels network intrusion detection system.Karbala Int.J. Mod.Sci.2015,1, 15–25.
Rajasekharaiah, K.; Dule, C. S.; Sudarshan, E. Cyber Security Challenges and its Emerging Trends on Latest Technologies. In Proceedings of the International Conference on Recent Advancements in Engineering and Management (ICRAEM-2020), Warangal, India, 9–10 October 2020.
Papamartzivanos,D.;Mármol,F.G.;Kambourakis,G.Dendron:Genetictreesdrivenruleinductionfornetworkintrusion detection systems.Future Gener.Comput.Syst.2018, 79, 558–574.
Kabir, E.; Hu, J.; Wang, H.; Zhuo, G. A novel statistical technique for intrusion detection systems.Future Gener.Comput.Syst. 2018, 79, 303–318.
Salih, A.A.; Adnan Mohsin, A. Evaluation of classification algorithms for intrusion detection system:A review.J. Soft Comput. Data Min.2021, 2, 31–40.
Palma,A.;Pereira,P.R.;Pereira,P.R.;Casaca,A.MulticastroutingprotocolforVehicularDelay-TolerantNetworks. InProceedingsofthe2012IEEE8thInternationalConferenceonWirelessandMobileComputing,NetworkingandCommunications(WiMob),Barcelona,Spain,8–10October2012;pp. 753–760.
Hemanand, D., Reddy, G. ., Babu, S. S. ., Balmuri, K. R. ., Chitra, T., & Gopalakrishnan, S. (2022). An Intelligent Intrusion Detection and Classification System using CSGO-LSVM Model for Wireless Sensor Networks (WSNs). International Journal of Intelligent Systems and Applications in Engineering, 10(3), 285–293. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2167
P. Satyanarayana, U. D. Yalavarthi, Y. S. S. Sriramam, M. Arun, V. G. Krishnan and S. Gopalakrishnan, "Implementation of Enhanced Energy Aware Clustering Based Routing (EEACBR)Algorithm to Improve Network Lifetime in WSN’s," 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, Karnataka, India, 2022, pp. 1-6, doi: 10.1109/ICMNWC56175.2022.10031991.
Gopalakrishnan Subburayalu, Hemanand Duraivelu, Arun Prasath Raveendran, Rajesh Arunachalam, Deepika Kongara & Chitra Thangavel (2023) Cluster Based Malicious Node Detection System for Mobile Ad-Hoc Network Using ANFIS Classifier, Journal of Applied Security Research, 18:3, 402-420, DOI: 10.1080/19361610.2021.2002118
Satyanarayana, P., Diwakar, G., Subbayamma, B. V., Phani Sai Kumar, N. V., Arun, M., & Gopalakrishnan, S. (2023). Comparative analysis of new meta-heuristic-variants for privacy preservation in wireless mobile adhoc networks for IoT applications. Computer Communications, 198, 262–281. https://doi.org/10.1016/j.comcom.2022.12.006
Perumal, G., Subburayalu, G., Abbas, Q., Naqi, S. M., & Qureshi, I. (2023). VBQ-Net: A Novel Vectorization-Based Boost Quantized Network Model for Maximizing the Security Level of IoT System to Prevent Intrusions. Systems, 11(8), 436. MDPI AG. Retrieved from http://dx.doi.org/10.3390/systems11080436
Turaka, R., Chand, S. R., Anitha, R., Prasath, R. A., Ramani, S., Kumar, H., Gopalakrishnan, S., &Farhaoui, Y. (2023). A novel approach for design energy efficient inexact reverse carry select adders for IoT applications. Results in Engineering, 18, 101127. https://doi.org/10.1016/j.rineng.2023.101127
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