Securing Vehicular Internet of Things (V-IoT) Communication in Smart VANET Infrastructure using Multi-layered Communication Framework and Novel Threat Detection Algorithm
Keywords:
Security, V-IoT, VANETs, Threat Detection, Edge Computing, AuthenticationAbstract
In latest technological paradigm, the incorporation of Vehicular Ad-Hoc Networks (VANETs) architecture with the Internet of Things (IoT) devices in smart transportation systems has introduced new proportions to reliable data communication. However, ensuring secured dynamic addition of IoT nodes and mitigating probable threats like Denial of Service (DoS) attacks, eavesdropping and malware poses a serious challenge in ensuring an efficient communication links. The VANET-IoT (V-IoT) system offers increased addition of IoT devices and its associated scalability but the increasing device usage to maintain low-latent connectivity poses serious threat and highly exposes the infrastructure to attacks. The need for secured node authentication in V-IoT is hence found essential to ease the deployment of new sensing devices without compromising on security. Conventional methods fails to offer a holistic approach in V-IoT system that combines authentication and threat detection via edge computing to ensure the communication reliability and security in V-IoT system. This research proposes a novel multi-layered V-IoT smart infrastructure with various components including authentication, IoT device integration, edge computing, and intelligent threat classification to maintain secured and efficient communication. An Evolutionary Multimodal Optimization (EMO) based Probabilistic Adversarial Ada-Transform (PAAT), a cutting-edge algorithm act as an authenticator and threat classifier in identifying DoS attacks, malware, and eavesdropping attempts in V-IoT systems. This multi-layered framework enables edge computing technology to append EMO-PAAT on V-IoT system for authentication and threat detection. Various parameters including scalability; algorithm performance; and V-IoT performance is measured via different metrics like Processing Time, Throughput, CPU and Memory Utilization, Latency; Detection Rate; and Communication Overhead, and Energy Consumption, respectively are utilized to evaluate the performance. Thus, significant improvements are reported in V-IoT system to maintain a secured and reliable communication.
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Memon, I., Hasan, M. K., Shaikh, R. A., Nebhen, J., Bakar, K. A. A., Hossain, E., & Tunio, M. H. (2021). Energy-efficient fuzzy management system for internet of things connected vehicular ad hoc networks. Electronics, 10(9), 1068.
Gupta, Sunil, Hitesh Kumar Sharma, and Monit Kapoor. Blockchain for Secure Healthcare Using Internet of Medical Things (IoMT). Springer, 2022.
Soni, Dheresh, Deepak Srivastava, Ashutosh Bhatt, Ambika Aggarwal, Sunil Kumar, and Mohd Asif Shah. "An Empirical Client Cloud Environment to Secure Data Communication with Alert Protocol." Mathematical Problems in Engineering (2022).
Aggarwal, Ambika, P. Dimri, and A. Agarwal. "Survey on scheduling algorithms for multiple workflows in cloud computing environment." International Journal on Computer Science and Engineering 7, no. 6 (2019): 565-570.
Gupta, Sunil, Hitesh Kumar Sharma, and Monit Kapoor. "Introduction to Smart Healthcare and Telemedicine Systems." In Blockchain for Secure Healthcare Using Internet of Medical Things (IoMT), pp. 1-11. Cham: Springer International Publishing, 2022.
Agarwal, Ambika, Neha Bora, and Nitin Arora. "Goodput enhanced digital image watermarking scheme based on DWT and SVD." International Journal of Application or Innovation in Engineering & Management 2, no. 9 (2013): 36-41.
Aggarwal, Ambika, Priti Dimri, and Amit Agarwal. "Statistical performance evaluation of various metaheuristic scheduling techniques for cloud environment." Journal of Computational and Theoretical Nanoscience 17, no. 9-10 (2020): 4593-4597.
Mahmoudian, M., Zanjani, S. M., Shahinzadeh, H., Kabalci, Y., Kabalci, E., & Ebrahimi, F. (2023, June). The Intelligent Mechanism for Data Collection and Data Mining in the Vehicular Ad-Hoc Networks (VANETs) Based on Big-Data-Driven. In 2023 5th Global Power, Energy and Communication Conference (GPECOM) (pp. 495-500). IEEE.
Swessi, D., & Idoudi, H. (2022). A survey on internet-of-things security: threats and emerging countermeasures. Wireless Personal Communications, 124(2), 1557-1592.
Chaudhary, Rajat, Prem Singh, and Ambika Agarwal. "A security solution for the transmission of confidential data and efficient file authentication based on DES, AES, DSS and RSA." International Journal of Innovative Technology and Exploring Engineering 1, no. 3 (2012): 5-11.
Xie, L., Ding, Y., Yang, H., & Wang, X. (2019). Blockchain-based secure and trustworthy Internet of Things in SDN-enabled 5G-VANETs. IEEE Access, 7, 56656-56666.
Awan, K. A., Din, I. U., Almogren, A., Guizani, M., & Khan, S. (2020). StabTrust—A stable and centralized trust-based clustering mechanism for IoT enabled vehicular ad-hoc networks. Ieee Access, 8, 21159-21177.
Alhaj, A. A., Zanoon, N. I., Alrabea, A., Alnatsheh, H. I., Jawabreh, O., Abu-Faraj, M., & Ali, B. J. (2023). Improving the Smart Cities Traffic Management Systems using VANETs and IoT Features.
Din, I. U., Ahmad, B., Almogren, A., Almajed, H., Mohiuddin, I., & Rodrigues, J. J. (2020). Left-right-front caching strategy for vehicular networks in icn-based internet of things. IEEE Access, 9, 595-605.
Ahmed, A., Abdullah, S., Iftikhar, S., Ahmad, I., Ajmal, S., & Hussain, Q. (2022). A novel blockchain based secured and QoS aware IoT vehicular network in edge cloud computing. IEEE Access, 10, 77707-77722.
Iqbal, S., Zafar, N. A., Ali, T., & Alkhammash, E. H. (2022). Efficient IoT-based formal model for vehicle-life interaction in VANETs using VDM-SL. Energies, 15(3), 1013.
Haris, M., Shah, M. A., & Maple, C. (2023). Internet of intelligent vehicles (IoIV): an intelligent VANET based computing via predictive modeling. IEEE Access.
Thumbur, G., Rao, G. S., Reddy, P. V., Gayathri, N. B., Reddy, D. K., & Padmavathamma, M. (2020). Efficient and secure certificateless aggregate signature-based authentication scheme for vehicular ad hoc networks. IEEE Internet of Things Journal, 8(3), 1908-1920.
Gad, A. R., Nashat, A. A., & Barkat, T. M. (2021). Intrusion detection system using machine learning for vehicular ad hoc networks based on ToN-IoT dataset. IEEE Access, 9, 142206-142217.
Zhou, Z., Gaurav, A., Gupta, B. B., Lytras, M. D., & Razzak, I. (2021). A fine-grained access control and security approach for intelligent vehicular transport in 6g communication system. IEEE transactions on intelligent transportation systems, 23(7), 9726-9735.
Chattaraj, D., Bera, B., Das, A. K., Saha, S., Lorenz, P., & Park, Y. (2021). Block-CLAP: Blockchain-assisted certificateless key agreement protocol for internet of vehicles in smart transportation. IEEE Transactions on Vehicular Technology, 70(8), 8092-8107.
DDoS Dataset, Available at: https://www.kaggle.com/datasets/devendra416/ddos-datasets, Accessed on 1.9.2023
Sebastian Garcia, Agustin Parmisano, & Maria Jose Erquiaga. (2020). IoT-23: A labeled dataset with malicious and benign IoT network traffic (Version 1.0.0) [Data set]. Zenodo. Available at: https://www.stratosphereips.org/datasets-iot23, Accessed on 1.9.2023
Mayya, A., Mitev, M., Chorti, A., & Fettweis, G. (2023). A SKG Security Challenge: Indoor SKG Under an On-The-Shoulder Eavesdropping Attack. arXiv preprint arXiv:2305.09251, Available at: https://ieee-dataport.org/documents/dataset-paper-skg-security-challenge-indoor-skg-under-shoulder-eavesdropping-attack, Accessed on 1.9.2023
Beemkumar, N., Gupta, S., Bhardwaj, S., Dhabliya, D., Rai, M., Pandey, J.K., Gupta, A. Activity recognition and IoT-based analysis using time series and CNN (2023) Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries, pp. 350-364.
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