Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Adaptive Quantum-Safe Cryptography for 6G Vehicular Networks via Context-Aware Optimization

Poushali Sengupta, Mayank Raikwar, Sabita Maharjan, Frank Eliassen, Yan Zhang

TL;DR

The paper tackles the challenge of quantum threats to V2X communications within stringent URLLC budgets. It introduces CAAP, a context-aware adaptive PQC framework that selects among lattice-, code-, and hash-based PQC configurations using short-term context forecasts and an adaptive multi-objective optimizer (APMOEA), complemented by a secure monotonic upgrade protocol. Key contributions include adaptive PQC planning with stability guarantees, a secure transition mechanism that resists downgrade and desynchronization, and comprehensive trace-driven evaluation demonstrating latency reductions and overhead savings while maintaining security. This work enables practical deployment of quantum-safe cryptography in 6G vehicular networks by balancing cryptographic security with real-time latency requirements in dynamic environments.

Abstract

Powerful quantum computers in the future may be able to break the security used for communication between vehicles and other devices (Vehicle-to-Everything, or V2X). New security methods called post-quantum cryptography can help protect these systems, but they often require more computing power and can slow down communication, posing a challenge for fast 6G vehicle networks. In this paper, we propose an adaptive post-quantum cryptography (PQC) framework that predicts short-term mobility and channel variations and dynamically selects suitable lattice-, code-, or hash-based PQC configurations using a predictive multi-objective evolutionary algorithm (APMOEA) to meet vehicular latency and security constraints.However, frequent cryptographic reconfiguration in dynamic vehicular environments introduces new attack surfaces during algorithm transitions. A secure monotonic-upgrade protocol prevents downgrade, replay, and desynchronization attacks during transitions. Theoretical results show decision stability under bounded prediction error, latency boundedness under mobility drift, and correctness under small forecast noise. These results demonstrate a practical path toward quantum-safe cryptography in future 6G vehicular networks. Through extensive experiments based on realistic mobility (LuST), weather (ERA5), and NR-V2X channel traces, we show that the proposed framework reduces end-to-end latency by up to 27\%, lowers communication overhead by up to 65\%, and effectively stabilizes cryptographic switching behavior using reinforcement learning. Moreover, under the evaluated adversarial scenarios, the monotonic-upgrade protocol successfully prevents downgrade, replay, and desynchronization attacks.

Adaptive Quantum-Safe Cryptography for 6G Vehicular Networks via Context-Aware Optimization

TL;DR

The paper tackles the challenge of quantum threats to V2X communications within stringent URLLC budgets. It introduces CAAP, a context-aware adaptive PQC framework that selects among lattice-, code-, and hash-based PQC configurations using short-term context forecasts and an adaptive multi-objective optimizer (APMOEA), complemented by a secure monotonic upgrade protocol. Key contributions include adaptive PQC planning with stability guarantees, a secure transition mechanism that resists downgrade and desynchronization, and comprehensive trace-driven evaluation demonstrating latency reductions and overhead savings while maintaining security. This work enables practical deployment of quantum-safe cryptography in 6G vehicular networks by balancing cryptographic security with real-time latency requirements in dynamic environments.

Abstract

Powerful quantum computers in the future may be able to break the security used for communication between vehicles and other devices (Vehicle-to-Everything, or V2X). New security methods called post-quantum cryptography can help protect these systems, but they often require more computing power and can slow down communication, posing a challenge for fast 6G vehicle networks. In this paper, we propose an adaptive post-quantum cryptography (PQC) framework that predicts short-term mobility and channel variations and dynamically selects suitable lattice-, code-, or hash-based PQC configurations using a predictive multi-objective evolutionary algorithm (APMOEA) to meet vehicular latency and security constraints.However, frequent cryptographic reconfiguration in dynamic vehicular environments introduces new attack surfaces during algorithm transitions. A secure monotonic-upgrade protocol prevents downgrade, replay, and desynchronization attacks during transitions. Theoretical results show decision stability under bounded prediction error, latency boundedness under mobility drift, and correctness under small forecast noise. These results demonstrate a practical path toward quantum-safe cryptography in future 6G vehicular networks. Through extensive experiments based on realistic mobility (LuST), weather (ERA5), and NR-V2X channel traces, we show that the proposed framework reduces end-to-end latency by up to 27\%, lowers communication overhead by up to 65\%, and effectively stabilizes cryptographic switching behavior using reinforcement learning. Moreover, under the evaluated adversarial scenarios, the monotonic-upgrade protocol successfully prevents downgrade, replay, and desynchronization attacks.
Paper Structure (20 sections, 4 theorems, 12 equations, 9 figures, 5 tables, 2 algorithms)

This paper contains 20 sections, 4 theorems, 12 equations, 9 figures, 5 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background, Related Work, and Threat Model
  3. Background and Related Work
  4. Threat Model
  5. Context aware Adaptive PQC (CAAP) Framework
  6. Relation to the MAPE-K Adaptation Loop
  7. V2X System Model and Vehicular Dynamics
  8. Context Model and Notation
  9. Secure PQC Transition Protocol
  10. APMOEA Optimization Algorithm
  11. Theoretical Guarantees
  12. Experimental Evaluation
  13. Conclusion
  14. Proofs of Theoretical Results
  15. Proof of Decision Stability
  16. ...and 5 more sections

Key Result

Theorem 5.1

If $K\varepsilon < \Delta_{\min}$, then APMOEA selects the same algorithm $a_t$ for all $t$ within a context-stable interval. Here, $K$ denotes the Lipschitz constant of the loss function, $\varepsilon$ is the context-prediction error, and $\Delta_{\min}$ is the minimum loss gap between any two PQC

Figures (9)

  • Figure 1: CAAP framework structured according to the MAPE-K control loop.
  • Figure 2: PQC version-upgrade protocol with monotonic transitions.
  • Figure : (a) Context-manipulation effect
  • Figure : (a) Upgrade vs downgrade
  • Figure : (a) Context-manipulation effect
  • ...and 4 more figures

Theorems & Definitions (8)

  • Theorem 5.1: Decision Stability
  • Theorem 5.2: Monotonic Upgrade Security
  • Theorem 5.3: Latency Boundedness
  • proof
  • proof
  • proof
  • Lemma A.1: Robustness Under Small Prediction Error
  • proof