6Gセンシングセキュリティ：都市ビームフォーミングと攻撃者検出のための分散ゲーム理論RL
6G Sensing Security: Distributed Game-Theoretic RL for Urban Beamforming and Attacker Detection
6Gの統合センシング・通信(ISAC)環境で、ビームフォーミングを操作する攻撃者を検出するため、ゲーム理論と強化学習を組み合わせた手法を提案し、シミュレーションで有効性を示した。
著者: Parmida Geranmayeh, Onur Günlü
分類: cs.IT, cs.CR, cs.GT, cs.LG, cs.NI
原文アブストラクト
In next-generation networks, communication systems will no longer be limited to data transmission and will be expected to acquire awareness of the surrounding environment. This leads to the concept of integrated sensing and communication (ISAC), where the same wireless infrastructure is used for both communication and environmental sensing. Thus, ISAC enables the system to transmit information efficiently and observe and interpret channel variations and user behavior. Motivated by this capability, this work focuses on detecting an active attacker in an urban environment scenario, where the attacker intentionally manipulates beamforming directions to increase interference and mislead the transmitter into allocating the main lobe of beam toward itself instead of legitimate users. We apply game-theoretic approaches to model the interaction between legitimate users and the attacker, and integrate the resulting utility-based formulation into a reinforcement learning (RL) framework. Simulation results demonstrate that the proposed method effectively addresses security challenges in dynamic 6G ISAC systems.