基于安全多方计算的实用隐私保护定位OA

Location-based services serve as the foundation for applications in various fields such as smart cities,traffic navigation,and military reconnaissance.However,existing positioning methods based on satellites,RFID,and WLAN often suffer from issues like location privacy leakage for both users and service providers,as well as low indoor positioning accuracy.To address these issues,this paper proposes a privacy-preserving localization scheme based on secure multi-party computation.The scheme defines a multi-party privacy protection model for range-based localization environments,safe-guarding the location information of all participants,including users and localization service providers.This paper introduces secret sharing techniques to split the location information of anchor nodes into multiple shares distributed among different nodes,ensuring mutual confidentiality during information exchange.Furthermore,this paper proposes a garbling scheme incorporating garbled circuit technology to optimize data representation and computation processes through obfuscated encoding of user location-related data,thereby ensuring that the user's location information remains confidential to the local-ization service providers.Simulation results demonstrate that the proposed scheme achieves high positioning accuracy and maintains strong robustness even in complex scenarios such as sparse anchor node distribution.Moreover,it improves 13%and 9%compared with the existing methods in terms of positioning communication volume and positioning efficiency,respectively.