Abstract: In indoor localization services, WiFi fingerprinting technology has received widespread attention due to its extensive coverage  and high localization accuracy. However, for the online phase of location query, the user’s personal sensitive information is vulnerable to malicious attacks resulting in location privacy leakage. Existing WiFi fingerprintbased indoor positioning technologies primarily focus on single flat surfaces within indoor environments, which restricts the flexibility of WiFi deployment. When WiFi is deployed in multidimensional scenarios, addressing spatial location privacy issues becomes imperative. In this paper, a WiFi fingerprinting indoor localization privacy protection scheme based on geographic indistinguishability is proposed, in which the user generates a new received signal strength vector by using his own received signal strength and sends the obtained data to the location service provider through noise obfuscation, and introduces a digital signature technique to ensure that the client’s identity is not forged before obfuscating the position to be sent to the location service provider to achieve localization. Experimental results based on the simulation experimental platform show that the new scheme supports flexible deployment of WiFi, and is able to realize highprecision localization for the first time in the case of flexible deployment of 12 WiFi access points with guaranteed localization error of less than 1m while protecting location privacy.

Key words: WiFi fingerprint indoor localization, locationbased service, privacy protection, differential privacy, geographic indistinguishability

摘要： 在室内定位服务中，WiFi指纹技术因其覆盖面积广、定位精度高而受到人们的广泛关注.然而，对于在线阶段的位置查询，用户的个人敏感信息容易受到恶意攻击而造成位置隐私泄露.现有基于WiFi指纹的室内定位技术仅考虑室内单一空旷平面，这使得WiFi部署的灵活性受到限制.而当WiFi部署在多维场景时，空间位置隐私问题亟待解决.提出了一种基于地理不可区分性的WiFi指纹室内定位隐私保护方案，用户利用自身接收信号强度生成一个新的接收信号强度向量，并通过加噪混淆将得到的数据发送给位置服务提供商，同时引入数字签名技术，在混淆位置被发送给位置服务提供商实现定位之前确保客户端身份不被伪造.基于模拟实验平台的实验结果表明，该方案支持WiFi的灵活部署，能够在保护位置隐私的同时，首次实现12个WiFi接入点灵活部署情况下的高精度定位，保证定位误差小于1m.

关键词: WiFi指纹室内定位, 位置服务, 隐私保护, 差分隐私, 地理不可区分性