位置服务中隐私偏好查询与隐藏关键技术研究

The constraint of privacy preference burdens the trade-off between location privacy protection and quality of service in privacy-aware location based service: 1.Privacy preferences contradict with privacy models diametrically in terms of personality and commonality they focus on, respectively. 2.There is a dilemma between privacy preferences and query performance that preferences require intermediate query results be dynamic and adjustable, while simplified intermediate query results commonly promise good performances. 3.Privacy preferences incur the attack originated from intersection inferring to candidate answer sets in continuous location based queries. 4.In privacy-aware trajectory publication, privacy preferences present in the manner of dynamic time and space constraints while the clustering utility of trajectories relies on the inherent time and space constraints contained in those trajectories. This kind of opposition intensifies the conflict between hiding trajectories and maintaining clustering utility. In response to these issues: 1.Privacy preferences are well formalized from view of the minimum inferred region and candidate answer region. Location privacy model and trajectory model are established incorporating privacy preferences and quality of the service. A quantifiable measurement mechanism is devised to measure effect of various kinds of location privacy protection schemes. 2.A user controllable model is developped to regulate relations between users' preferred minimum inferred regions and regions of candidate answers. Data synopsis and compression functions of space filling technologies are explored to alleviate loss of query performance originated from users' privacy preferences. 3.To avoid candidate answer set attacks in privacy-aware continuous queries, location privacy models with dual levels are introduced and realized via building the safe region scheme of anchor points. 4. A two-way obfuscation strategy is developped leveraging dividing and conquering idea to address the conflicts mentioned earlier in privacy-aware trajectory publishing incorporating users' preferences. It benefits from accommodating the inherent time and space constraints and the externally imposed dynamic ones from horizontal and vertical levels of the trajectories. The scheme can well meet the requirements of supporting users' privacy preferences and maintaining clustering utility of trajectory data set. Our work devotes to compensate for current research of privacy-aware location based service in neglecting privacy preference supporting or its poverty at seeking trade-off between personalized users' privacy preferences and the quality of location based services.

隐私敏感位置服务中位置隐私与服务质量的兼顾在隐私偏好约束下尤为困难：1.偏好强调个性与隐私模型侧重共性存在矛盾；2.偏好对查询中间结果动态可控依赖与查询简化中间结果思想相抵触；3.连续查询中支持隐私偏好存在候选解集拆分攻击风险；4.偏好对时空约束的动态要求与轨迹聚类可用性依赖静态约束对立，激化了隐藏轨迹与维持聚类可用性间矛盾。针对上述问题：1.从最小逆推区域、候选解区域角度描述隐私偏好，构建兼顾偏好与服务质量的隐私模型及位置安全量化度量机制；2.构建基于位置扰动的最小逆推区域、候选解区域调控模型，发掘空间填充技术的数据概要功效以兼顾隐私偏好与查询性能；3.引入双层位置隐私模型并构建假位置安全区域机制，避免候选解集拆分攻击；4.提出基于分治的双向隐藏策略解决支持隐私偏好与维持轨迹聚类可用性间彰显个性与保存共性的冲突。弥补现有研究弱化隐私偏好，难以兼顾个性化偏好与服务质量的不足。

随着位置服务的日益普及，人们在享受位置服务带来便利的同时也日益关注位置服务中的隐私保护问题。本项目研究位置服务中的隐私偏好问题，以期推进隐私保护位置服务研究的深入和走向实用。.项目组遵照研究计划，对保护位置隐私查询与轨迹隐藏中的偏好问题展开研究。在隐私模型方面，提出了基于侯选解区域与最小逆推区域面积的位置隐私模型，支持查询发起者对位置隐私的偏好调控要求，在此基础上提出了基于熵的位置隐私模型和前瞻位置隐私模型，并提出相应位置泛化方法；通过解析保护位置隐私近邻查询中隐私安全性和查询效率间的制约关系，提出了结合位置扰动与隐式空间混淆的支持偏好调控的保护位置隐私近邻查询框架；对保护位置隐私瞬时近邻查询，根据路网与非路网环境约束，提出了一系列基于位置扰动、空间混淆以及隐秘信息检索（PIR）的查询方法，支持查询效率、位置隐私强度和查询准确性间的调控；对保护位置隐私连续查询，解析非路网环境连续查询中存在的“中垂线攻击”问题，提出基于所构建隐私模型的保护位置隐私连续近邻查询方法，支持查询效率与隐私保护强度动态调控；进一步，关注路网环境连续查询发起时机问题，提出路网安全区域概念，给出支持偏好调控的路网保护位置隐私连续近邻查询策略，该策略可以兼容已有基于路网混淆的保护位置隐私近邻查询方法；在轨迹隐藏方面，兼顾偏好调控要求，提出基于扰动和分组的轨迹隐藏发布方案；在位置隐私保护强度度量方面，引入条件熵矩阵定义，提出了基于条件熵和操作分解的位置隐私保护强度度量方案。.目前，研究任务总体上已完成，主要研究成果已发表或撰文投稿中。后续，将进一步深化总结研究成果，进行更广泛的国内外交流，积极寻求研究成果的产业应用机会。