TC: Small: Location-Privacy Protection for Mobile Handset Users

越来越多地使用智能手机和基于位置的服务(LBS)来执行他们的工作和非工作功能，这可能会诱使用户泄露他们的位置和移动信息，这些信息可能被对手利用来推断他们访问的兴趣点(POI)，从而推断他们的隐私信息。为了保护移动用户的位置隐私，本项目将首先提高对移动用户位置隐私面临的新威胁和攻击的理解。在了解了这一点后，它将开发、实施和评估一个高效且有效的框架，称为位置信息加扰器(LISA)，该框架可以调整用户位置的不确定性，从而消除--或显著削弱--S可能访问的POI的可区分性。这个项目具有以下智力价值。通过在每个移动用户的设备上本地保护位置隐私，LISA将不会依赖现有方法通常需要的可信第三方服务器；这消除了单点故障漏洞，并促进了其实施和部署。此外，由于能源效率是能源匮乏的移动设备最关键的要求，该项目将开发出在位置隐私和能源消耗之间进行权衡的方法，以自适应地在隐私保护和能源消耗之间实现平衡。目前，位置隐私是一个非常主观的概念，其定义千差万别。为了加深对位置隐私的理解，并制定有效的位置隐私保护措施，本项目包括(1)基于m-不可观测性的位置隐私的形式化定义；(2)收集真实世界中人和车辆的移动模式的痕迹，并通过分析这些痕迹建立不同的移动和跟踪模型；(3)优化移动用户的位置隐私水平与移动用户设备的能耗之间的权衡；(4)根据用户的偏好和情况自适应配置位置隐私需求，以优化能量消耗；(5)使用LISA增强用户的移动设备，以保护他们的位置隐私，而不需要任何现有方法依赖的可信第三方服务器；(6)通过在20名志愿者的智能手机上实施和部署LISA来评估LISA的效果和效率。这项研究还将通过提高快速增长的使用智能手机和LBS进行日常功能的人数的安全性和工作效率，产生更广泛的影响。拟议的研究、推广和教育活动的整合将对安全研究和行业社区产生社会和教育影响，保护移动用户的隐私，提高对移动服务和网络安全的认识，并开发熟练的人力资源。

Increasing use of smartphones and location-based services (LBSs) for their on- and off-job functions will likely entice users to reveal their location and movement information, which may be exploited by adversaries to infer the Points of Interest (POIs) they visit, and hence their privacy information. To protect mobile users' location privacy, this project will first improve the understanding of emerging threats and attacks against their location privacy. With this understanding, it will then develop, implement, and evaluate an efficient and effective framework, called the Location Information ScrAmbler (LISA), that adjusts uncertainty in a user's location, thereby removing -- or significantly weakening -- the distinguishability of the POIs s/he may visit. This project has intellectual merit as follows. By protecting location privacy locally on each mobile user's device, LISA will not rely on trusted third-party servers commonly required by existing approaches; this removes single-point-of-failure vulnerabilities and facilitates its implementation and deployment. Moreover, since energy-efficiency is the most critical requirement for energy-deficient mobile devices, this project will develop ways of making a trade-off between location privacy and energy consumption to adaptively achieve a balance between privacy protection and energy consumption. At present, location privacy is a very subjective concept with widely-varying definitions. To advance the understanding of, and develop effective measures for location privacy and protection, this project consists of (1) formal definition of location privacy based on the notion of m-unobservability; (2) collection of real-world traces of human and vehicle mobility pattern, and development of different mobility and tracking models by analyzing the traces; (3) optimization of the trade-off between the level of a mobile user's location privacy and energy consumption by the mobile user's device; (4) adaptive configuration of the location-privacy requirements according to the user's preference and situation so as to optimize energy consumption; (5) augmentation of users' mobile devices with LISA to protect their location privacy without requiring any trusted third-party server that most existing approaches rely on; (6) comprehensive field experiments to evaluate the efficacy and efficiency of LISA by implementing and deploying it to 20 some volunteers' smartphones. This research will also make broader impacts by improving both the security and productivity of a rapidly-growing number of people who use smartphones and LBSs for their daily functions. The proposed integration of research, outreach, and education activities will have social and educational impacts on the security research and industry communities, protecting mobile users' privacy, increasing the awareness of mobile service and network security, and developing skilled human resources.