移动位置服务中基于隐私关注的用户行为模式与保护机制研究

Mobile location-based services (LBS), as mobile commerce "killer" applications, can provide customers with personalized services, but also leak user's location private information, which may bring about privacy concerns and perceived risk. So privacy has become a "double-edged sword" of LBS services. How to identify the composition and influence factors of privacy concerns based on the privacy concern and context, and how to implement the effective privacy protection mechanism and promote the user behaviors have become focuses of current researches. But most researches focus on technology and algorithm without paying enough attention to the privacy cognition, user behaviors and context changes. Therefore, this project firstly proposes a cognitive process model of privacy concern in LBS services to explore the key factors affecting the privacy concerns, and their mutual relation and the dynamic impact. Secondly, the project comes up with the methods of privacy information management and protection in LBS services, and designs multi source heterogeneous privacy information and privacy information protection model based on privacy concern and context. Thirdly, based on user behaviors and countermeasures of privacy concern, the project analyses the impact of privacy concern, personalized services and context factors on the user behavior in LBS services, and examines privacy concern changes when the privacy protection is embedded in the system. To sum up, the results can provide countermeasures and suggestions for users to alleviate privacy concerns and perceived risk, and promote the usage and further applications of LBS services.

作为移动商务"杀手锏"应用的移动位置服务（LBS）在向用户提供个性化服务的同时也易泄露用户位置等隐私信息，引发隐私忧虑和感知风险即隐私关注，隐私问题已成为发展LBS服务的一把"双刃剑"，如何识别隐私关注的构成和影响因素，如何基于隐私关注程度和情境实施有效的隐私保护机制和促进用户使用行为，已成为当前研究的焦点问题。为此，本项目研究提出①LBS服务中隐私关注的认知过程模型，研究隐私关注构成，探讨隐私关注影响因素，及其相互关系和动态影响；②面向LBS服务的隐私信息管理与保护方法，设计多源异构隐私信息管理方法、基于隐私关注程度和情境的隐私信息保护模型；③基于隐私关注的LBS用户行为与对策，分析隐私关注、个性化服务以及情境对用户使用LBS的作用，考察嵌入隐私保护系统前后隐私关注程度的变化。项目成果可为用户缓解隐私忧虑和感知风险提供对策和建议，促进用户使用行为，有助于进一步推动LBS服务的深层次应用。

随着普适计算技术的发展和移动应用的日益深入，作为移动商务“杀手锏”应用的移动位置服务（LBS）在向用户提供个性化服务的同时也易泄露用户位置等隐私信息，引发隐私忧虑和感知风险即隐私关注，隐私问题已成为发展LBS 服务的一把“双刃剑”，如何识别隐私关注的构成和影响因素，如何基于隐私关注程度和情境实施有效的隐私保护机制和促进用户使用行为，已成为当前研究的焦点问题。为此，本项目研究提出（1）LBS 服务中隐私关注的认知过程模型，研究了隐私关注构成，探讨隐私关注影响因素，及其相互关系和动态影响；（2）面向LBS 服务的隐私信息管理与保护方法，设计了多源异构隐私信息管理方法、基于隐私关注程度和情境的隐私信息保护模型；（3）基于隐私关注的LBS 用户行为与对策，分析了隐私关注、个性化服务以及情境对用户使用LBS 的作用，考察嵌入隐私保护系统前后隐私关注程度的变化。项目研究成果具体包括：（1）构建了LBS服务中隐私关注的认知过程模型，分析各要素之间的相互关系及动态影响，分析不同要素、情境对用户隐私关注的影响；（2）面向LBS服务的隐私信息管理方法，构建了面向移动位置服务的多源异构隐私信息集成与整合方法，有效集成整合多来源异构隐私信息；（3）构建了基于隐私关注的隐私信息保护模型，完善了基于隐私关注和情境变化的隐私信息保护与调整适应机制。总之，项目成果可为用户缓解隐私忧虑和感知风险提供对策和建议，促进用户使用行为，有助于进一步推动LBS 服务的深层次应用。