An RLWE-Based Privacy-Preserving Key Agreement Method for Offshore Wind Farms

Offshore wind farms are representative unmanned energy systems whose operation relies heavily on remote information exchange between offshore substations and onshore centralized control centers. However, the cross-sea communication link is vulnerable to cyberattacks, including impersonation and message tampering, and these threats persist in the quantum computing era, potentially compromising operational decision-making and control. To address this problem, this paper proposes a privacy-preserving key agreement method based on the Ring Learning With Errors (RLWE) problem. First, identity privacy protection is integrated with post-quantum cryptography. An identity commitment function conceals the true identities of the communicating entities, while a pre-shared authentication factor and fresh random parameters enable mutual authentication and session key establishment. This design prevents identity disclosure and secures information exchange in offshore wind farms against quantum-capable adversaries. Second, confidentiality and unforgeability are formally established under the decisional and search RLWE assumptions. Finally, experiments validate the effectiveness of the proposed method. Compared with existing schemes, it reduces communication overhead by up to 43.75%, making it particularly suitable for resource-constrained offshore wind farm environments.