Localization in mobile networks has been widely applied in many scenarios. However, an entity responsible for location estimation exposes both the target and anchors to potential location leakage at any time, creating serious security risks. Although existing studies have proposed privacy-preserving localization algorithms, they still face challenges of insufficient positioning accuracy and excessive communication overhead. In this article, we propose a privacy-preserving localization scheme, named PPLZN. PPLZN protects protects the location privacy of both the target and anchor nodes in crowdsourced localization. Simulation results validate the effectiveness of PPLZN. Evidently, it can achieve accurate position estimation without location leakage and outperform state-of-the-art approaches in both positioning accuracy and communication overhead. In addition, PPLZN significantly reduces computational and communication overhead in large-scale deployments, making it well-fitted for practical privacy-preserving localization in resource-constrained networks.

翻译：移动网络中的定位技术已在众多场景中得到广泛应用。然而，负责位置估计的实体可能随时暴露目标节点与锚节点的位置信息，导致严重的隐私泄露风险。尽管现有研究已提出多种隐私保护定位算法，但仍面临定位精度不足与通信开销过大的挑战。本文提出一种名为PPLZN的隐私保护定位方案。该方案在众包定位场景中同时保护目标节点与锚节点的位置隐私。仿真结果验证了PPLZN的有效性。实验表明，该方案能在避免位置泄露的前提下实现精确的位置估计，并在定位精度与通信开销方面均优于现有先进方案。此外，PPLZN在大规模部署中显著降低了计算与通信开销，使其特别适用于资源受限网络中的实际隐私保护定位场景。