Future Cars Shielded from Quantum Hacking with Adaptable Security System
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Researchers are addressing the critical vulnerability of future 6G vehicular networks to attacks from quantum computers. Poushali Sengupta, Mayank Raikwar, and Sabita Maharjan, from the University of Oslo, alongside Frank Eliassen and Yan Zhang, present a novel adaptive post-quantum cryptographic framework designed to secure Vehicle-to-Everything (V2X) communications. This work is significant because it overcomes the performance limitations typically associated with post-quantum cryptography through context-aware optimisation and predictive algorithms, reducing latency and communication overhead.
The team’s approach not only selects appropriate cryptographic configurations dynamically but also introduces a secure protocol to mitigate new attack surfaces arising from frequent cryptographic changes, paving the way for practical quantum-safe security in next-generation vehicular systems. Researchers have developed a system capable of dynamically selecting the most efficient cryptographic algorithms based on real-time conditions, addressing a critical vulnerability in vehicle-to-everything communication. This work introduces a Context-Aware Adaptive PQC framework that predicts short-term mobility and channel variations, enabling the selection of optimal lattice-, code-, or hash-based post-quantum configurations. The system balances the need for robust security with the stringent latency and bandwidth requirements of 6G networks, a challenge that has previously hindered the widespread adoption of post-quantum solutions. Central to this innovation is a predictive multi-objective evolutionary algorithm that anticipates vehicular context changes within 100, 200 millisecond windows. This algorithm considers factors such as vehicle speed, communication quality, weather conditions, and message urgency to optimise cryptographic choices for ultra-reliable low-latency communication. Furthermore, a secure monotonic-upgrade protocol prevents potential attacks during transitions between cryptographic algorithms, mitigating risks associated with reconfiguration. Theoretical analysis confirms decision stability under bounded prediction error, latency boundedness under mobility drift, and correctness under small forecast noise, demonstrating the framework’s reliability. Extensive experiments utilising realistic mobility traces, weather data, and channel models reveal significant performance improvements. The proposed framework reduces end-to-end latency by up to 27%, lowers communication overhead by up to 65%, and effectively stabilises cryptographic switching behaviour through reinforcement learning. Under evaluated adversarial scenarios, the monotonic-upgrade protocol successfully prevents downgrade, replay, and desynchronization attacks, ensuring the integrity of vehicular communications.
This research establishes a practical pathway toward quantum-safe cryptography in future 6G vehicular networks, without introducing novel cryptographic primitives, but rather optimising their application. Dynamic cryptographic configuration via short-term vehicular context prediction enhances security and privacy A predictive multi-objective evolutionary algorithm (APMOEA) forms the core of the proposed adaptive post-quantum cryptography (PQC) framework for 6G vehicular networks. This algorithm dynamically selects the most suitable PQC configuration, lattice-, code-, or hash-based, based on predicted vehicular mobility and channel variations. The research employed realistic mobility traces from the LuST dataset, weather information sourced from ERA5, and NR-V2X channel traces to simulate a comprehensive vehicular environment. The framework begins with a Context-Sensing Pipeline that gathers data on vehicle speed, communication quality, weather conditions, and message urgency, consolidating this information into a unified context vector. A Short-Term Predictor then anticipates context changes within 100, 200 millisecond windows, enabling proactive cryptographic adjustments. This predictive capability is crucial for minimizing latency and maintaining security in rapidly evolving vehicular scenarios. To ensure secure transitions between cryptographic algorithms, a monotonic-upgrade protocol was implemented. This protocol prevents downgrade, replay, and desynchronization attacks during algorithm switching, mirroring security principles found in TLS 1.3 and QUIC. The protocol authenticates version negotiation, guaranteeing that cryptographic configurations only advance to more secure states. Extensive experiments demonstrated that this protocol successfully mitigated adversarial attacks under evaluated scenarios. Performance was assessed by measuring end-to-end latency, communication overhead, and cryptographic switching stability. Results indicated that the proposed framework reduces end-to-end latency by up to 27 percent and lowers communication overhead by up to 65 percent. Reinforcement learning techniques were used to effectively stabilize cryptographic switching behavior, further enhancing the framework’s robustness and efficiency in dynamic vehicular environments. Theoretical analysis confirmed decision stability under bounded prediction error, latency boundedness under mobility drift, and correctness under small forecast noise, validating the framework’s practical viability. Adaptive post-quantum cryptography reduces latency and overhead in 6G vehicular networks by dynamically adjusting security levels A reduction of up to 27% in end-to-end latency was achieved through the implementation of an adaptive post-quantum cryptographic framework designed for 6G vehicle networks. This framework dynamically selects from lattice-, code-, or hash-based post-quantum cryptography configurations based on predicted short-term mobility and channel variations. The adaptive process utilizes a predictive multi-objective evolutionary algorithm to meet both vehicular latency and security requirements. Communication overhead was lowered by up to 65% by optimizing cryptographic choices to maintain ultra-reliable low-latency communication compliance. Extensive experiments incorporated realistic mobility data from LuST, weather information from ERA5, and channel traces compliant with NR-V2X standards to validate performance gains. Reinforcement learning effectively stabilized cryptographic switching behavior, ensuring consistent and reliable operation in dynamic vehicular environments. The secure monotonic-upgrade protocol successfully prevented downgrade, replay, and desynchronization attacks under evaluated adversarial scenarios. Theoretical analysis demonstrated decision stability under bounded prediction error, confirming the robustness of the adaptive algorithm. Latency boundedness was also proven under conditions of mobility drift, indicating predictable performance even with changing vehicle dynamics. Correctness of the PQC selection was verified under small forecast noise, demonstrating the framework’s resilience to imperfect predictions. This work establishes a practical pathway toward quantum-safe cryptography for future 6G vehicular networks, addressing the security vulnerabilities posed by emerging quantum computing capabilities. The research highlights a context-aware approach to cryptographic selection, optimizing for both security and performance in challenging vehicular environments. Dynamic cryptographic selection for low-latency secure 6G V2X communications enables adaptable and efficient security protocols An adaptive post-quantum cryptographic (PQC) framework has been developed for use in future 6G vehicle-to-everything (V2X) communications. This framework addresses the potential threat posed by quantum computers to current V2X security protocols by dynamically selecting appropriate cryptographic schemes based on predicted mobility and channel conditions. The system employs a predictive multi-objective evolutionary algorithm to balance latency and security requirements, ensuring efficient and secure data transmission. Experimental results, utilising realistic mobility, weather, and channel data, demonstrate a reduction in end-to-end latency of up to 27% and a decrease in communication overhead of up to 65%. A secure monotonic-upgrade protocol was also implemented to prevent attacks during transitions between cryptographic algorithms, successfully mitigating downgrade, replay, and desynchronization attempts under adversarial conditions. Theoretical analysis confirms the stability of decision-making and bounded latency even with realistic prediction errors and mobility fluctuations. The authors acknowledge that the current work focuses on optimising either encryption or signature schemes individually. Future research will extend the framework to jointly optimise both, reflecting the need for combined encryption and signature mechanisms in practical post-quantum security applications. Despite this limitation, the demonstrated reductions in latency and communication overhead, alongside the robust security protocol, represent a significant step towards establishing quantum-safe vehicular networks for 6G and beyond. 👉 More information 🗞 Adaptive Quantum-Safe Cryptography for 6G Vehicular Networks via Context-Aware Optimization 🧠 ArXiv: https://arxiv.org/abs/2602.01342 Tags: