Skip to main content

DDoS Attack Detection in Vehicular Ad-Hoc Network (VANET) for 5G Networks

  • Chapter
  • First Online:
Security and Privacy Preserving for IoT and 5G Networks

Part of the book series: Studies in Big Data ((SBD,volume 95))

Abstract

VANET is a crucial part of the intelligent transport system (ITS). VANET helps the vehicle nodes to exchange important and life-saving information, so any attack on VANET should be detected fast. The DDoS attack is one of the cyber-attacks that attack the availability of the VANET systems. Due to the DDoS attack vehicle nodes are not capable to exchange valuable information. In this chapter, we propose a fog-based DDoS detection approach that uses fuzzy logic to differentiate attack traffic from normal traffic in 5G-enabled smart cities. The proposed approach achieves more than 90% precision and true negative rate, it indicates that our proposed approach correctly identifies the DDoS attack traffic.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abd EL-Latif, A.A., Abd-El-Atty, B., Venegas-Andraca, S.E., Mazurczyk, W.: Efficient quantum-based security protocols for information sharing and data protection in 5G networks. Future Gener. Comput. Syst. 100, 893–906 (2019)

    Google Scholar 

  2. Abou-Nassar, E.M., Iliyasu, A.M., El-Kafrawy, P.M., Song, O.Y., Bashir, A.K., Abd El-Latif, A.A.: Ditrust chain: towards blockchain-based trust models for sustainable healthcare IoT systems. IEEE Access 8, 111223–111238 (2020)

    Article  Google Scholar 

  3. Adhikary, K., Bhushan, S., Kumar, S., Dutta, K.: Hybrid algorithm to detect DDoS attacks in vanets. Wirel. Person. Commun. 1–22 (2020)

    Google Scholar 

  4. Ahmed, S.H., Rani, S.: A hybrid approach, smart street use case and future aspects for internet of things in smart cities. Future Gener. Comput. Syst. 79, 941–951 (2018)

    Article  Google Scholar 

  5. Al-Nawasrah, A., Almomani, A.A., Atawneh, S., Alauthman, M.: A survey of fast flux botnet detection with fast flux cloud computing. Int. J. Cloud Appl. Comput. (IJCAC) 10(3), 17–53 (2020)

    Google Scholar 

  6. Al-Turjman, F.: 5G-enabled devices and smart-spaces in social-IoT: an overview. Future Gener. Comput. Syst. 92, 732–744 (2019)

    Article  Google Scholar 

  7. Alomari, E., Manickam, S., Gupta, B., Karuppayah, S., Alfaris, R.: Botnet-based distributed denial of service (DDoS) attacks on web servers: classification and art (2012). arXiv preprint arXiv:1208.0403

  8. AlZu’bi, S., Shehab, M., Al-Ayyoub, M., Jararweh, Y., Gupta, B.: Parallel implementation for 3D medical volume fuzzy segmentation. Pattern Recogn. Lett. 130, 312–318 (2020)

    Article  Google Scholar 

  9. Badve, O.P., Gupta, B.: Taxonomy of recent DDoS attack prevention, detection, and response schemes in cloud environment. In: Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processing, pp. 683–693. Springer (2016)

    Google Scholar 

  10. Behrisch, M., Bieker, L., Erdmann, J., Krajzewicz, D.: Sumo—simulation of urban mobility: an overview. In: Proceedings of SIMUL 2011, The Third International Conference on Advances in System Simulation. ThinkMind (2011)

    Google Scholar 

  11. Bello, O., Zeadally, S.: Toward efficient smartification of the internet of things (IoT) services. Future Gener. Comput. Syst. 92, 663–673 (2019)

    Article  Google Scholar 

  12. Benadda, M., Belalem, G.: Improving road safety for driver malaise and sleepiness behind the wheel using vehicular cloud computing and body area networks. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 12(4), 19–41 (2020)

    Article  Google Scholar 

  13. Bhushan, K., Gupta, B.B.: 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 (2019)

    Article  Google Scholar 

  14. Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing. pp. 13–16 (2012)

    Google Scholar 

  15. Chaudhary, R., Kumar, N., Zeadally, S.: Network service chaining in fog and cloud computing for the 5G environment: data management and security challenges. IEEE Commun. Mag. 55(11), 114–122 (2017)

    Article  Google Scholar 

  16. Chen, J., Ran, X.: Deep learning with edge computing: a review. Proc. IEEE 107(8), 1655–1674 (2019)

    Article  Google Scholar 

  17. Chettri, L., Bera, R.: A comprehensive survey on internet of things (IoT) toward 5D wireless systems. IEEE Internet Things J. 7(1), 16–32 (2019)

    Article  Google Scholar 

  18. Chhabra, M., Gupta, B., Almomani, A.: A novel solution to handle DDoS attack in manet (2013)

    Google Scholar 

  19. Cui, J., Wei, L., Zhong, H., Zhang, J., Xu, Y., Liu, L.: Edge computing in vanets-an efficient and privacy-preserving cooperative downloading scheme. IEEE J. Sel. Areas Commun. 38(6), 1191–1204 (2020)

    Article  Google Scholar 

  20. Dahiya, A., Gupta, B.: Multi attribute auction based incentivized solution against DDoS attacks. Comput. Secur. 92, 101763 (2020)

    Google Scholar 

  21. Dao, N.N., Park, M., Kim, J., Paek, J., Cho, S.: Resource-aware relay selection for inter-cell interference avoidance in 5G heterogeneous network for internet of things systems. Future Gener. Comput. Syst. 93, 877–887 (2019)

    Article  Google Scholar 

  22. Elgendy, I.A., Zhang, W.Z., He, H., Gupta, B.B., Abd El-Latif, A.A.: Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms. Wirel. Netw. 1–16 (2021)

    Google Scholar 

  23. Erskine, S.K., Elleithy, K.M.: Secure intelligent vehicular network using fog computing. Electronics 8(4), 455 (2019)

    Google Scholar 

  24. Fang, D., Qian, Y., Hu, R.Q.: Security for 5G mobile wireless networks. IEEE Access 6, 4850–4874 (2017)

    Article  Google Scholar 

  25. Ferrag, M.A., Maglaras, L., Argyriou, A., Kosmanos, D., Janicke, H.: Security for 4G and 5G cellular networks: a survey of existing authentication and privacy-preserving schemes. J. Netw. Comput. Appl. 101, 55–82 (2018)

    Article  Google Scholar 

  26. Gaurav, A., Gupta, B., Castiglione, A., Psannis, K., Choi, C.: A novel approach for fake news detection in vehicular ad-hoc network (vanet). In: International Conference on Computational Data and Social Networks. pp. 386–397. Springer (2020)

    Google Scholar 

  27. Gaurav, A., Singh, A.K.: Super-router: A collaborative filtering technique against DDoS attacks. In: International Conference on Advanced Informatics for Computing Research. pp. 294–305. Springer (2017)

    Google Scholar 

  28. Gaurav, A., Singh, A.K.: Light weight approach for secure backbone construction for manets. J. King Saud Univ. Comput. Inf. Sci. (2018)

    Google Scholar 

  29. Ghori, M.R., Zamli, K.Z., Quosthoni, N., Hisyam, M., Montaser, M.: Vehicular ad-hoc network (vanet). In: 2018 IEEE International Conference on Innovative Research and Development (ICIRD). pp. 1–6. IEEE (2018)

    Google Scholar 

  30. Gou, Z., Yamaguchi, S., Gupta, B.: Analysis of various security issues and challenges in cloud computing environment: a survey. In: Identity Theft: breakthroughs in Research and Practice, pp. 221–247. IGI global (2017)

    Google Scholar 

  31. Gu, K., Dong, X., Jia, W.: Malicious node detection scheme based on correlation of data and network topology in fog computing-based vanets. IEEE Trans. Cloud Comput. (2020)

    Google Scholar 

  32. Gudivada, A., Philips, J., Tabrizi, N.: Developing concept enriched models for big data processing within the medical domain. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 12(3), 55–71 (2020)

    Article  Google Scholar 

  33. Gupta, B.B., Joshi, R.C., Misra, M.: An efficient analytical solution to thwart DDoS attacks in public domain. In: Proceedings of the International Conference on Advances in Computing, Communication and Control. pp. 503–509 (2009)

    Google Scholar 

  34. Ji, X., Huang, K., Jin, L., Tang, H., Liu, C., Zhong, Z., You, W., Xu, X., Zhao, H., Wu, J., et al.: Overview of 5G Secur. Technolo. Sci. China Inf. Sci. 61(8), 1–25 (2018)

    Article  Google Scholar 

  35. Jover, R.P.: The current state of affairs in 5g security and the main remaining security challenges (2019). arXiv preprint arXiv:1904.08394

  36. Kamarudin, M.H., Maple, C., Watson, T.: Hybrid feature selection technique for intrusion detection system. Int. J. High Perform. Comput. Netw. 13(2), 232–240 (2019)

    Article  Google Scholar 

  37. Kaushik, S., Gandhi, C.: Ensure hierarchal identity based data security in cloud environment. Int. J. Cloud Appl. Comput. (IJCAC) 9(4), 21–36 (2019)

    Google Scholar 

  38. Khare, A.K., Rana, J., Jain, R.: Detection of wormhole, blackhole and ddos attack in manet using trust estimation under fuzzy logic methodology. Int. J. Comput. Netw. Inf. Secur. 9(7), 29 (2017)

    Google Scholar 

  39. Khayyat, M., Alshahrani, A., Alharbi, S., Elgendy, I., Paramonov, A., Koucheryavy, A.: Multilevel service-provisioning-based autonomous vehicle applications. Sustainability 12(6), 2497 (2020)

    Google Scholar 

  40. Khayyat, M., Elgendy, I.A., Muthanna, A., Alshahrani, A.S., Alharbi, S., Koucheryavy, A.: Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks. IEEE Access 8, 137052–137062 (2020)

    Article  Google Scholar 

  41. Kolandaisamy, R., Md Noor, R., Ahmedy, I., Ahmad, I., Reza Z’aba, M., Imran, M., Alnuem, M.: A multivariant stream analysis approach to detect and mitigate DDoS attacks in vehicular ad hoc networks. Wirel. Commun. Mob. Comput. 2018 (2018)

    Google Scholar 

  42. Kolandaisamy, R., Noor, R.M., Kolandaisamy, I., Ahmedy, I., Kiah, M.L.M., Tamil, M.E.M., Nandy, T.: A stream position performance analysis model based on ddos attack detection for cluster-based routing in vanet. J. Ambient Intell. Hum. Comput. 1–14 (2020)

    Google Scholar 

  43. Kumar, S., Mann, K.S.: Detection of multiple malicious nodes using entropy for mitigating the effect of denial of service attack in vanets. In: 2018 4th International Conference on Computing Sciences (ICCS), pp. 72–79. IEEE (2018)

    Google Scholar 

  44. Li, S., Da Xu, L., Zhao, S.: 5G internet of things: a survey. J. Ind. Inf. Integr. 10, 1–9 (2018)

    Google Scholar 

  45. Liu, Y., Peng, J., Kang, J., Iliyasu, A.M., Niyato, D., Abd El-Latif, A.A.: A secure federated learning framework for 5G networks. IEEE Wirel. Commun. 27(4), 24–31 (2020)

    Article  Google Scholar 

  46. Mani, N., Moh, M., Moh, T.S.: Defending deep learning models against adversarial attacks. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 13(1), 72–89 (2021)

    Article  Google Scholar 

  47. Mukherjee, M., Matam, R., Shu, L., Maglaras, L., Ferrag, M.A., Choudhury, N., Kumar, V.: Security and privacy in fog computing: challenges. IEEE Access 5, 19293–19304 (2017)

    Article  Google Scholar 

  48. Nkenyereye, L., Liu, C.H., Song, J.: Towards secure and privacy preserving collision avoidance system in 5G fog based internet of vehicles. Future Gener. Comput. Syste. 95, 488–499 (2019)

    Article  Google Scholar 

  49. Peng, H., Shen, X.S.: Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks. IEEE Trans. Netw. Sci. Eng. (2020)

    Google Scholar 

  50. Ponikwar, C., Hof, H.J.: Overview on security approaches in intelligent transportation systems (2015). arXiv preprint arXiv:1509.01552

  51. RoselinMary, S., Maheshwari, M., Thamaraiselvan, M.: Early detection of DOS attacks in vanet using attacked packet detection algorithm (APDA). In: 2013 International Conference on Information Communication and Embedded Systems (ICICES). pp. 237–240. IEEE (2013)

    Google Scholar 

  52. Rudraraju, C.: Simulation of Detecting and Preventing DDoS in Vehicular Ad-hoc Networks (VANETS). Ph.D. thesis, Dublin, National College of Ireland (2020)

    Google Scholar 

  53. Sarivougioukas, J., Vagelatos, A.: Modeling deep learning neural networks with denotational mathematics in ubihealth environment. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 12(3), 14–27 (2020)

    Article  Google Scholar 

  54. Sarrab, M., Alshohoumi, F.: Assisted-fog-based framework for IoT-based healthcare data preservation. Int. J. Cloud Appl. Comput. (IJCAC) 11(2), 1–16 (2021)

    Google Scholar 

  55. Schinianakis, D.: Alternative security options in the 5G and IoT era. IEEE Circuits Syst. Mag. 17(4), 6–28 (2017)

    Article  Google Scholar 

  56. Sedik, A., Hammad, M., Abd El-Samie, F.E., Gupta, B.B., Abd El-Latif, A.A.: Efficient deep learning approach for augmented detection of coronavirus disease. Neural Comput. Appl. 1–18 (2021)

    Google Scholar 

  57. Shakshuki, E.M., Kang, N., Sheltami, T.R.: EAACK—a secure intrusion-detection system for MANETs. IEEE Trans. Ind. Electron. 60(3), 1089–1098 (2012)

    Article  Google Scholar 

  58. Shidaganti, G.I., Inamdar, A.S., Rai, S.V., Rajeev, A.M.: SCEF: a model for prevention of DDOS attacks from the cloud. Int. J. Cloud Appl. Comput. (IJCAC) 10(3), 67–80 (2020)

    Google Scholar 

  59. Singh, A., Sharma, P.: A novel mechanism for detecting dos attack in vanet using enhanced attacked packet detection algorithm (eapda). In: 2015 2nd International Conference on Recent Advances in Engineering Computational Sciences (RAECS), pp. 1–5 (2015)

    Google Scholar 

  60. Singh, A., Kumar, R.: A two-phase load balancing algorithm for cloud environment. Int. J. Softw. Sci. Comput. Intell. (IJSSCI) 13(1), 38–55 (2021)

    Article  Google Scholar 

  61. Sk, A., Masilamani, V.: A novel digital watermarking scheme for data authentication and copyright protection in 5G networks. Comput. Electr. Eng. 72, 589–605 (2018)

    Article  Google Scholar 

  62. Sodhro, A.H., Pirbhulal, S., Sangaiah, A.K., Lohano, S., Sodhro, G.H., Luo, Z.: 5G-based transmission power control mechanism in fog computing for internet of things devices. Sustainability 10(4), 1258 (2018)

    Google Scholar 

  63. Sommer, C., German, R., Dressler, F.: Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans. Mob. Comput. 10(1), 3–15 (2010)

    Article  Google Scholar 

  64. Sun, J., Gu, Q., Zheng, T., Dong, P., Valera, A., Qin, Y.: Joint optimization of computation offloading and task scheduling in vehicular edge computing networks. IEEE Access 8, 10466–10477 (2020)

    Article  Google Scholar 

  65. Tanwar, S., Vora, J., Tyagi, S., Kumar, N., Obaidat, M.S.: A systematic review on security issues in vehicular ad hoc network. Secur. Priv. 1(5), e39 (2018)

    Google Scholar 

  66. Tupakula, U., Varadharajan, V., Mishra, P.: Securing SDN controller and switches from attacks. Int. J. High Perform. Comput. Netw. 14(1), 77–91 (2019)

    Article  Google Scholar 

  67. Varga, A.: A practical introduction to the omnet++ simulation framework. In: Recent Advances in Network Simulation, pp. 3–51. Springer (2019)

    Google Scholar 

  68. Wang, J., Feng, D., Zhang, S., Tang, J., Quek, T.Q.: Computation offloading for mobile edge computing enabled vehicular networks. IEEE Access 7, 62624–62632 (2019)

    Article  Google Scholar 

  69. Wang, X., Ning, Z., Wang, L.: Offloading in internet of vehicles: a fog-enabled real-time traffic management system. IEEE Trans. Ind. Inform. 14(10), 4568–4578 (2018)

    Article  Google Scholar 

  70. Xu, X., Xue, Y., Qi, L., Yuan, Y., Zhang, X., Umer, T., Wan, S.: An edge computing-enabled computation offloading method with privacy preservation for internet of connected vehicles. Future Gener. Comput. Syst. 96, 89–100 (2019)

    Article  Google Scholar 

  71. Yan, Z., Xie, H., Zhang, P., Gupta, B.B.: Flexible data access control in D2D communications. Future Gener. Comput. Syst. 82, 738–751 (2018)

    Article  Google Scholar 

  72. Yang, S., Yin, D., Song, X., Dong, X., Manogaran, G., Mastorakis, G., Mavromoustakis, C.X., Batalla, J.M.: Security situation assessment for massive MIMO systems for 5G communications. Future Gener. Comput. Syst. 98, 25–34 (2019)

    Article  Google Scholar 

  73. Ye, H., Li, G.Y., Juang, B.H.F.: Deep reinforcement learning based resource allocation for V2V communications. IEEE Trans. Veh. Technol. 68(4), 3163–3173 (2019)

    Article  Google Scholar 

  74. Zhan, W., Luo, C., Wang, J., Wang, C., Min, G., Duan, H., Zhu, Q.: Deep-reinforcement-learning-based offloading scheduling for vehicular edge computing. IEEE Internet Things J. 7(6), 5449–5465 (2020)

    Article  Google Scholar 

  75. Zhang, W.Z., Elgendy, I.A., Hammad, M., Iliyasu, A.M., Du, X., Guizani, M., Abd El-Latif, A.A.: Secure and optimized load balancing for multi-tier IoT and edge-cloud computing systems. IEEE Internet Things J. (2020)

    Google Scholar 

  76. Zhao, J., Li, Q., Gong, Y., Zhang, K.: Computation offloading and resource allocation for cloud assisted mobile edge computing in vehicular networks. IEEE Trans. Veh. Technol. 68(8), 7944–7956 (2019)

    Article  Google Scholar 

  77. Zhou, H., Chen, X., He, S., Chen, J., Wu, J.: DRAIM: a novel delay-constraint and reverse auction-based incentive mechanism for WiFi offloading. IEEE J. Sel. Areas Commun. 38(4), 711–722 (2020)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gaurav, A., Gupta, B.B., Peñalvo, F.J.G., Nedjah, N., Psannis, K. (2022). DDoS Attack Detection in Vehicular Ad-Hoc Network (VANET) for 5G Networks. In: Abd El-Latif, A.A., Abd-El-Atty, B., Venegas-Andraca, S.E., Mazurczyk, W., Gupta, B.B. (eds) Security and Privacy Preserving for IoT and 5G Networks. Studies in Big Data, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-030-85428-7_11

Download citation

Publish with us

Policies and ethics