Design and Evaluation of Secure Software Architectures for 5G-Enabled Vehicular Driving System
DOI:
https://doi.org/10.18196/jrc.v6i4.26032Keywords:
Post-Quantum Cryptography, Vehicular Ad-hoc Networks (VANETs), Fog Computing, Software Architectures, Mutual Authentication, 5G Network SecurityAbstract
Vehicular Ad-hoc Networks (VANETs) represent support for Intelligent Transport Systems (ITS) that allow vehicles and infrastructures to exchange real-time information. Nevertheless, the introduction of the 5G technology for the VANETs poses new security challenges, especially considering the emerging quantum computing threats. In response to this problem, we present a secure software architecture, Lattice Efficient Mutual Authentication (LEMA), designed to improve vehicular communication in 5G supported environments. The research novelty is the construction of LEMA—a lightweight and scalable framework for robust authentication in the fog, based on lattice-based postquantum cryptography, which is also resilient to classical and quantum-based attacks and provides low latency. The framework operates based on three core phases: initialization by a Trusted Authority, secure private key generation, and mutual authentication via LWE-based schemes. A testbed which is built on a Raspberry Pi is used for simulating OBUs to verify LEMA performance in a resource-constrained environment. We compare LEMA with the state of art and get the performance numbers for the computational overhead, communication cost and storage efficiency. Simulation results show that with LEMA, the computational time, the communication amount and the storage consumed can be decreased by at least 25%, 30% and 20% than the benchmark protocols, respectively, and it is secure against the man-in-themiddle and the key-compromise attacks. The authors’ use of fog servers for deployment of the system also significantly boosts real-time responsiveness. Finally, the LEMA model presents a promising quantum-secure authentication technique for 5G-based vehicular networks. In the future we plan to combine it with AIbased anomaly detection and blockchain, for better scalability, privacy and decentralization.
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