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RETRACTED ARTICLE: A stream position performance analysis model based on DDoS attack detection for cluster-based routing in VANET

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This article was retracted on 23 June 2022

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Abstract

The strength of Vehicular Ad hoc Networks (VANETs) and the rapid deployment capability, can be used in many situations where the network should be arranged in a short time and there is a need to collect sensitive information. We consider cluster-based attack detection in data compilation wherever the neighbor nodes give the important information to the cluster head. Moreover, evidence is obtainable in the cluster head may possibly be accumulated by some vehicular nodes and executes numerous responsibilities such as decision making about delivering information. The existence of malicious nodes threatens determination making through transmitting malevolent information, which is not appropriate to the VANET categorized data and might send a substantial number of packets to the vehicles or Road Side Unit (RSU). To overcome this issue, we have proposed a Stream Position Performance Analysis (SPPA) approach. This approach monitors the position of any field station in sending the information to perform a Distributed Denial of Service (DDoS) attack. The method computes various factors like Conflict field, Conflict data and Attack signature sample rate (CCA). Using all these factors, the method identifies the trustworthiness of the packet and includes it in decision making. The proposed approach increases the performance of a Distributed Denial of Service (DDoS) attack detection in a VANET environment.

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References

  • Ahmad I, Ahmad I, Imran M, Sattar K, Shoaib M, Nasir M (2017) Towards intrusion detection to secure VANET-assisted healthcare monitoring system. J Med Imaging Health Inform 7(6):1391–1398

    Article  Google Scholar 

  • Balan EV, Priyan MK, Gokulnath C, Devi GU (2015) Fuzzy based intrusion detection systems in MANET. Procedia Comput Sci 50:109–114

    Article  Google Scholar 

  • Bhushan K, Gupta BB (2019) Distributed denial of service (DDoS) attack mitigation in software defined network (SDN)-based cloud computing environment. J Ambient Intell Hum Comput 10(5):1985–1997

    Article  Google Scholar 

  • Cheng J, Tang X, Yin J (2017) A change-point DDoS attack detection method based on half interaction anomaly degree. Int J Auton Adapt Commun Syst 10(1):38–54

    Article  Google Scholar 

  • Chikhaoui O, Chehida AB, Abassi R, El Fatmi SG (2017) A ticket-based authentication scheme for vanets preserving privacy. In: International conference on ad-hoc networks and wireless. Springer, Cham, pp 77–91

  • de Biasi G, Vieira LF, Loureiro AA (2018) Sentinel: defense mechanism against DDoS flooding attack in software defined vehicular network. In: 2018 IEEE international conference on communications (ICC). IEEE, pp 1–6

  • Fotohi R, Ebazadeh Y, Geshlag MS (2016) A new approach for improvement security against DoS attacks in vehicular ad-hoc network. Int J Adv Comput Sci Appl 7(7):10–16

    Google Scholar 

  • Fragkiadakis AG, Siris VA, Petroulakis NE, Traganitis AP (2015) Anomaly-based intrusion detection of jamming attacks, local versus collaborative detection. Wirel Commun Mob Comput 15(2):276–294

    Google Scholar 

  • Fung CJ, Zhu Q (2016) FACID: A trust-based collaborative decision framework for intrusion detection networks. Ad Hoc Netw 53:17–31

    Article  Google Scholar 

  • Gupta BB, Joshi RC, Misra M (2012) Distributed denial of service prevention techniques. arXiv:1208.3557

  • Hasrouny H, Samhat AE, Bassil C, Laouiti A (2017) VANet security challenges and solutions: a survey. Veh Commun 7:7–20

    Google Scholar 

  • Jalil AB, Kolandaisamy R, Subaramaniam K, Kolandaisamy I (2020) Designing a mobile application to improve user’s productivity on computer-based productivity software. J Adv Res Dyn Control Syst 12(3):226–236

    Article  Google Scholar 

  • Kaur M, Mahajan M (2015) A novel security approach for data flow and data pattern analysis to mitigate DDoS attacks in VANETs. Int J Hybrid Inf Technol 8(8):113–122

    Google Scholar 

  • Kolandaisamy R, Md Noor R, Ahmedy I, Ahmad I, Reza Z’aba M, Imran M, Alnuem M (2018) A multivariant stream analysis approach to detect and mitigate DDoS attacks in vehicular ad hoc networks. In: Wireless communications and mobile computing, 2018.

  • Kolandaisamy R, Noor RM, Z’aba MR, Ahmedy I, Kolandaisamy I (2019a) Adapted stream region for packet marking based on DDoS attack detection in vehicular ad hoc networks. J Supercomput, 1–23

  • Kolandaisamy R, Noor RM, Zaba MR, Ahmedy I, Kolandaisamy I (2019b) Markov chain based ant colony approach for mitigating DDoS attacks using integrated vehicle mode analysis in VANET. In: 2019 IEEE 1st international conference on energy, systems and information processing (ICESIP). IEEE, pp 1–5

  • Lyamin N, Vinel A, Jonsson M, Loo J (2014) Real-time detection of denial-of-service attacks in IEEE 802.11 p vehicular networks. IEEE Commun Lett 18(1):110–113

    Article  Google Scholar 

  • Nadeem A, Howarth MP (2014) An intrusion detection and adaptive response mechanism for MANETs. Ad Hoc Netw 13:368–380

    Article  Google Scholar 

  • Panjeta S, Aggarwal EK, Student PG (2017) Review paper on different techniques in combination with IDS. Int J Eng Sci

  • Pathre A, Agrawal C, Jain A (2013) A novel defense scheme against DDOS attack in VANET. In: 2013 Tenth international conference on wireless and optical communications networks (WOCN). IEEE, pp 1–5

  • Pillutla H, Arjunan A (2019) Fuzzy self organizing maps-based DDoS mitigation mechanism for software defined networking in cloud computing. J Ambient Intell Hum Comput 10(4):1547–1559

    Article  Google Scholar 

  • Sangulagi P, Sarsamba M, Talwar M, Katgi V (2013) Recognition and elimination of malicious nodes in vehicular ad hoc networks (VANET’s). Indian J Comput Sci Eng 4(1).

  • Saritha V, Krishna PV, Misra S, Obaidat MS (2017) Learning automata based optimized multipath routing using leapfrog algorithm for VANETs. In: 2017 IEEE international conference on communications (ICC). IEEE, pp 1–5

  • Shah SAA, Ahmed E, Imran M, Zeadally S (2018) 5G for vehicular communications. IEEE Commun Mag 56(1):111–117

    Article  Google Scholar 

  • Shakshuki EM, Isiuwe S (2018) Resource management approach to an efficient wireless sensor network. Proced Comput Sci 141:190–198

    Article  Google Scholar 

  • Shakshuki EM, Kang N, Sheltami TR (2013) EAACK—a secure intrusion-detection system for MANETs. IEEE Trans Ind Electron 60(3):1089–1098

    Article  Google Scholar 

  • Wang X, Guo N, Gao F, Feng J (2019) Distributed denial of service attack defence simulation based on honeynet technology. J Ambient Intell Hum Comput, 1–16

  • Xiang M, Chen Y, Ku WS, Su Z (2011) Mitigating DDOS attacks using protection nodes in mobile Ad hoc networks. In: 2011 IEEE global telecommunications conference-GLOBECOM 2011. IEEE, pp 1–6

  • Yaqoob I, Ahmed E, Ur Rehman MH, Ahmed AIA, Al-garadi MA, Imran M, Guizani M (2017) The rise of ransomware and emerging security challenges in the Internet of Things. Comput Netw 129:444–458

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in partnership grant between the University of Malaya and Sunway University under Grant RK004-2017 and in part of RU Grants (Under Faculties) GPF004D-2019; and the Pioneer Scientist Incentive Fund (PSIF), UCSI University, through Research Grant no: Proj-2019-In-FOBIS-023.

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Correspondence to Raenu Kolandaisamy or Rafidah Md Noor.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s12652-022-04213-0

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Kolandaisamy, R., Noor, R.M., Kolandaisamy, I. et al. RETRACTED ARTICLE: A stream position performance analysis model based on DDoS attack detection for cluster-based routing in VANET. J Ambient Intell Human Comput 12, 6599–6612 (2021). https://doi.org/10.1007/s12652-020-02279-2

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