Abstract
Now-a-days, with the augmenting accident statistics, the Vehicular Ad-hoc Networks (VANET) are turning out to be more popular, helping in prevention of accidents in addition to damage to the vehicles together with populace. In VANET, message can well be transmitted within a pre-stated region to attain system’s safety and also improve its efficacy. Ensuring authenticity of messages’ is a challenge in such dynamic environment. Though few researchers worked on this, security level is very less. Hence enhanced communication security on the VANET environment utilizing the American Standard Code for Information Interchange centred Elliptic Curve Cryptography (ASCII-ECC) is proposed in this paper. The network design is defined initially. Subsequently, the entire vehicles get registered to the Trusted Authority (TA); similarly, all vehicle users are registered with their On-Board Unit (OBU). This is followed by Median-centred K-Means (MKM) performs the cluster formation together with Cluster Head Selection (CHS). Next, TA takes care of the verification procedure. Modified Cockroach Swarm Optimization (MCSO) calculates the shortest path and the ASCII-ECC carries out the secure data communication if the vehicle is an authorized one. If not, TA sends the alert message for discarding the request. The system renders better performance when it was weighed against the top-notch methods.
Similar content being viewed by others
Availability of Data and Material (Data transparency)
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
Code Availability
Software application or custom code:NA.
References
Khatri, S., Vachhani, H., Shah, S., Bhatia, J., Chaturvedi, M., Tanwar, S., & Kumar, N. (2020). Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges. Peer-to-Peer Networking and Applications. https://doi.org/10.1007/s12083-020-00993-4
Zhou, H., Wang, H., Chen, X., Li, X., & Shouzhi, Xu. (2018). Data offloading techniques through vehicular ad hoc networks: A survey. IEEE Access, 6, 65250–65259.
Garg, S., Singh, A., Kaur, K., Aujla, G. S., Batra, S., Kumar, N., & Obaidat, M. S. (2019). Edge computing-based security framework for big data analytics in VANETs. IEEE Network, 33(2), 72–81.
Arif, M., Guojun Wang, Md., Bhuiyan, Z. A., Wang, T., & Chen, J. (2019). A survey on security attacks in VANETs: Communication, applications and challenges. Vehicular Communications, 19, 100179.
Manivannan, D., Moni, S. S., & Zeadally, S. (2020). Secure authentication and privacy-preserving techniques in vehicular ad-hoc networks (VANETs). Vehicular Communications, 25, 100247. https://doi.org/10.1016/j.vehcom.2020.100247
Hussain, R., Bouk, S. H., Javaid, N., Khan, A. M., & Lee, J. (2018). Realization of VANET-based cloud services through named data networking. IEEE Communications Magazine, 56(8), 168–175.
Hande, R.S, & Muddana, A. (2016) Comprehensive survey on clustering-based efficient data dissemination algorithms for VANET. In IEEE international conference on signal processing, communication, power and embedded system (SCOPES), pp. 629–632, https://doi.org/10.1109/SCOPES.2016.7955516.
Liu, L., Chen, C., Qiu, T., Zhang, M., Li, S., & Zhou, B. (2018). A data dissemination scheme based on clustering and probabilistic broadcasting in VANETs. Vehicular Communications, 13, 78–88.
Khattak, H. A., Islam, S. U., Din, I. U., & Guizani, M. (2019). Integrating fog computing with VANETs: A consumer perspective. IEEE Communications Standards Magazine, 3(1), 19–25.
Wan, C., & Zhang, J. (2018). Efficient identity-based data transmission for VANET. Journal of Ambient Intelligence and Humanized Computing, 9(6), 1861–1871.
Malik, N., Nanda. P., Arora, A., He, X., & Puthal, D. (2018) Blockchain based secured identity authentication and expeditious revocation framework for vehicular networks. In 17th IEEE international conference on trust, security and privacy in computing and communications/12th international conference on big data science and engineering (TrustCom/BigDataSE), pp. 674–679, https://doi.org/10.1109/TrustCom/BigDataSE.2018.00099.
Garip, M.T., Reiher, P., & Gerla, M. (2018) Botveillance: A vehicular botnet surveillance attack against pseudonymous systems in vanets. In IEEE 11th IFIP wireless and mobile networking conference (WMNC), pp. 1–8, https://doi.org/10.23919/WMNC.2018.8480909.
Rashdan, I., de Ponte Muller, F., & Sand, S. (2016) Performance evaluation of traffic information dissemination protocols for dynamic route planning application in VANETs. In IEEE 84th vehicular technology conference (VTC-Fall), pp. 1–5, https://doi.org/10.1109/VTCFall.2016.7881161.
Rawat, D.B., Bista, B.B, & Yan, G. (2016) Securing vehicular ad-hoc networks from data falsification attacks. In IEEE region 10 conference (TENCON), pp. 99–102, https://doi.org/10.1109/TENCON.2016.7847967.
Lyamin, N., Kleyko, D., Delooz, Q., & Vinel, A. (2018). AI-based malicious network traffic detection in VANETs. IEEE Network, 32(6), 15–21.
Boukerche, A., Tao, Y., & Sun, P. (2020). Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems. Computer Networks, 182, 107484.
Khalid, A., Umer, T., Afzal, M. K., Anjum, S., Sohail, A., & Asif, H. (2018). Autonomous data driven surveillance and rectification system using in-vehicle sensors for intelligent transportation systems (ITS). Computer Networks, 139, 109–118.
Manickam P., Shankar, K., Perumal, E., Ilayaraja, M., & Kumar, K.S. (2019) Secure data transmission through reliable vehicles in VANET using optimal lightweight cryptography, Cybersecurity and secure information systems. Springer, Cham, pp. 193–204, https://doi.org/10.1007/978-3-030-16837-7_9.
Sharma, P., Liu, H., Wang, H., & Zhang, S. (2017) Securing wireless communications of connected vehicles with artificial intelligence. In IEEE international symposium on technologies for homeland security (HST), pp. 1–7, https://doi.org/10.1109/THS.2017.7943477.
Tang, Y., Cheng, N., Wen, Wu., Wang, M., Dai, Y., & Shen, X. (2019). Delay-minimization routing for heterogeneous VANETs with machine learning based mobility prediction. IEEE Transactions on Vehicular Technology, 68(4), 3967–3979.
Dai, C., Xiao, X., Ding, Y., Xiao, L., Tang, Y., & Zhou, S. (2018) Learning based security for VANET with blockchain. In IEEE international conference on communication systems (ICCS), pp. 210–215, https://doi.org/10.1109/ICCS.2018.8689228.
Kudva, S., Badsha, S., Sengupta, S., Khalil, I., & Zomaya, A. (2020). Towards secure and practical consensus for blockchain based VANET. Information Sciences, 545, 170–187.
Roy, A., & Madria, S. (2020) Distributed incentive-based secured traffic monitoring in VANETs. In 21st IEEE international conference on mobile data management (MDM), pp. 49–58, https://doi.org/10.1109/MDM48529.2020.00026.
Bhatia, J., Kakadia, P., Bhavsar, M., & Tanwar, S. (2019). SDN-enabled network coding based secure data dissemination in VANET environment. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2019.2956964
Tyagi, P., & Dembla, D. (2018). Advanced secured routing algorithm of vehicular ad-hoc network. Wireless Personal Communications, 102(1), 41–60.
Jenefa, J., & Mary Anita, E. A. (2021). Identity-based message authentication scheme using proxy vehicles for vehicular ad hoc networks. Wireless Networks. https://doi.org/10.1007/s11276-021-02655-6
Acknowledgements
We thank the anonymous referees for their useful suggestions.
Funding
There has been no financial support for this work that could have influences its outcomes.
Author information
Authors and Affiliations
Contributions
All Authors contributed for preparation and analysis as performed in ASCII-ECC algorithm. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
No conflicts of interests associated with this publication.
Consent for publication
We declare that this manuscript is original has not been published before and is not currently being considered for publication elsewhere.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Sajini, S., Anita, E.A.M. & Janet, J. Improved Security of the Data Communication in VANET Environment Using ASCII-ECC Algorithm. Wireless Pers Commun 128, 759–776 (2023). https://doi.org/10.1007/s11277-022-09974-7
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-022-09974-7