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Lecture notes in computer science

Game Theoretic Security Framework for Quantum Key Distribution

Walter O. Krawec, Fei Miao

Published Jan 1, 2018• 2 citations
Publisher
DOI
10.1007/978-3-030-01554-1_3

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We present a parallel device independent quantum key distribution (DIQKD) protocol based on the CHSH game and prove its security. Using techniques developed for analysing the parallel repetition of anchored non-local games, we show that the answers on a small random linear subset of the games in the DIQKD protocol can be simulated as the output of a single-round strategy for playing the CHSH game. Then, we use the recently developed unstructured approximate entropy accumulation theorem to establish the smooth min-entropy lower bound required for the security proof. Our approach yields a more information-theoretic and general proof for parallel DIQKD compared to previous proofs.
Quantum key distribution (QKD) enables secure communication for vehicular networks, but its range limitation calls for multi-hop relaying. Unmanned aerial vehicles (UAVs) can serve as flexible QKD relays, yet their selfish behavior and dynamic mobility pose significant challenges. This paper proposes a secure routing framework for UAV-assisted vehicular QKD that jointly addresses incentive compatibility and path reliability. We model the interaction between the source vehicle and UAVs as a Stackelberg game, where the source sets the relay reward and UAVs decide their participation. A smoothed relay path formulation ensures differentiability and equilibrium tractability. To enable decentralized learning of relay strategies, we adopt a multi-agent deep deterministic policy gradient (MADDPG) algorithm. Furthermore, a Bayesian optimization module is integrated to adaptively search for the optimal reward value that maximizes the source vehicle's utility. Simulation results show that the proposed Stackelberg-MADDPG-Bayesian scheme outperforms existing baselines in terms of relay request success rate and secure key generation rate, and remains robust under various UAV selfishness levels and network dynamics.