基于空间k-匿名的位置隐私保护技术研究
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摘要
近年来，具备全球定位系统GPS (Global Positioning System)和互联网功能的移动设备已经变得非常普遍，人们使用这些设备通过基于位置的服务LBS (Location-BasedServices)可以很方便地获取所需的信息。但人们在享受这些服务的同时，也引发了严重的隐私问题，因为LBS需要依据用户的地理位置检索信息。如果攻击者知晓用户的精确位置，那么他可能从用户的查询位置(如医院等)推测出敏感信息。因此，当人们使用LBS时有必要引入位置隐私保护机制。对于不同的隐私保护目标和不同的攻击模型，有着不同的保护方法，其中大多数方法利用空间k-匿名的概念保护用户隐私。这些方法通常基于可信第三方TTP (Trusted Third Parties)组件实现匿名。
文中首先系统评估了现有位置隐私保护方法的适用性和有效性，引入了攻击分类，并分析了现有方法的保护目标和抗攻击能力。然后基于用户—匿名器—LBS架构，分别针对欧氏空间和路网环境的位置隐私保护、常见查询等问题进行了研究。具体内容如下。
首先，提出了空间k-匿名共匿算法。不仅保证了共匿性要求，而且由于采用通用的空间索引技术，如R*-树或Quard-树，所以在保证匿名要求的同时，还支持其它类型的查询。在此基础上，提出了一种新型调节中值分割方法，以提高查询效率和有效性。并且文中还提出了一种基于位置敏感哈希分割的空间k-匿名算法，该算法具有保距性和适度的计算复杂度，还可以作为分割方法来使用。
其次，提出了路网环境下移动服务隐私保护的通用模型StarGCloaking。主要有三个特性：支持路网、个性化隐私和服务质量QoS (Quality of Service)需求；在抗攻击能力和匿名查询的处理成本方面取得平衡；基于星图的隐私保护模式以及多重优化实现，支持大量移动用户不同的服务需求。
再次，提出保护路网用户隐私的隐匿算法HSGCloaking。通过将星形网络节点进行希尔伯特排序满足每个用户的共匿条件。框架支持k-最近邻居k-NN (k-NearestNeighbor)和范围查询，并提出了这两种常见查询的处理算法。
最后，基于理论分析和实验验证，证明了上述算法的正确性和有效性。
In recent years, mobile devices enabled with GPS and Internet access have becomeextremely common. People use these devices to obtain information easily through locationbased services (LBS). Although these services are very popular, their usage can also raisesevere privacy concerns because LBS provides customized information based on a user’sgeographic location. For example, an adversary may infer sensitive information fromprecise user positions (such as hospital). Therefore, mechanisms for protecting locationprivacy are mandatory when using LBSs. Available location privacy approaches differwith respect to the protected information and the considered attacker model. Most of themimplement the concept of k-anonymity to protect the user’s privacy. These methodsusually rely on the use of trusted third parties (TTP) such as anonymous servers.
This thesis assess the applicability and effectiveness of location privacy approachessystematically firstly. A classification of possible attacks that try to reveal the protectedinformation introduced. It analyzes existing approaches with respect to their protectiongoals and their ability to resists the introduced attacks. Then it implements researches onsome key issues such as location privacy protection, general queries in Euclidean spaceand road network condition based on user-anonymizer-LBS framework. The completeresearch is outlined below:
Firstly, a general framework for implementing reciprocal algorithms using anyexisting spatial index (such as R*-trees and Quad-trees) on the user locations is proposed.Moreover, since employing general-purpose spatial indices, the proposed system is notlimited to anonymization, but supports conventional spatial queries as well. At the sametime, an adjusted median splits method is provided, aimed on effectiveness and efficiency.And a spatial k-anonymity algorithm based on locality-sensitive hashing partition isproposed. The algorithm is shown to preserve both locality and moderate computationcomplexity. It can also be used as splits method.
Secondly, a general model for privacy-aware mobile services over road networks(StarGCloaking) is proposed. StarGCloaking has three distinct features: it supports road-network-specific, personalized privacy and quality of service (QoS) requirements ona per request basis; it strikes a balance between the attack resilience of the performedprotection and the processing cost of the anonymous query; it scales to support a largenumber of mobile users with varying service requirements, through a star-graph basedprivatization model, powered by multi-folded optimizations in implementation.
Thirdly, an HSGCloaking algorithm to protect users’ privacy in road network isproposed. It orders the nodes of a star network by using Hilbert order to meet thereciprocity condition of every user. The cloaking framework supports k-nearest neighbor(k-NN) and range queries by presenting two query processing algorithms.
Finally, the correctness and validity of the above algorithms are proved by thetheoretical analysis and experimental verification.
文中首先系统评估了现有位置隐私保护方法的适用性和有效性，引入了攻击分类，并分析了现有方法的保护目标和抗攻击能力。然后基于用户—匿名器—LBS架构，分别针对欧氏空间和路网环境的位置隐私保护、常见查询等问题进行了研究。具体内容如下。
首先，提出了空间k-匿名共匿算法。不仅保证了共匿性要求，而且由于采用通用的空间索引技术，如R*-树或Quard-树，所以在保证匿名要求的同时，还支持其它类型的查询。在此基础上，提出了一种新型调节中值分割方法，以提高查询效率和有效性。并且文中还提出了一种基于位置敏感哈希分割的空间k-匿名算法，该算法具有保距性和适度的计算复杂度，还可以作为分割方法来使用。
其次，提出了路网环境下移动服务隐私保护的通用模型StarGCloaking。主要有三个特性：支持路网、个性化隐私和服务质量QoS (Quality of Service)需求；在抗攻击能力和匿名查询的处理成本方面取得平衡；基于星图的隐私保护模式以及多重优化实现，支持大量移动用户不同的服务需求。
再次，提出保护路网用户隐私的隐匿算法HSGCloaking。通过将星形网络节点进行希尔伯特排序满足每个用户的共匿条件。框架支持k-最近邻居k-NN (k-NearestNeighbor)和范围查询，并提出了这两种常见查询的处理算法。
最后，基于理论分析和实验验证，证明了上述算法的正确性和有效性。
In recent years, mobile devices enabled with GPS and Internet access have becomeextremely common. People use these devices to obtain information easily through locationbased services (LBS). Although these services are very popular, their usage can also raisesevere privacy concerns because LBS provides customized information based on a user’sgeographic location. For example, an adversary may infer sensitive information fromprecise user positions (such as hospital). Therefore, mechanisms for protecting locationprivacy are mandatory when using LBSs. Available location privacy approaches differwith respect to the protected information and the considered attacker model. Most of themimplement the concept of k-anonymity to protect the user’s privacy. These methodsusually rely on the use of trusted third parties (TTP) such as anonymous servers.
This thesis assess the applicability and effectiveness of location privacy approachessystematically firstly. A classification of possible attacks that try to reveal the protectedinformation introduced. It analyzes existing approaches with respect to their protectiongoals and their ability to resists the introduced attacks. Then it implements researches onsome key issues such as location privacy protection, general queries in Euclidean spaceand road network condition based on user-anonymizer-LBS framework. The completeresearch is outlined below:
Firstly, a general framework for implementing reciprocal algorithms using anyexisting spatial index (such as R*-trees and Quad-trees) on the user locations is proposed.Moreover, since employing general-purpose spatial indices, the proposed system is notlimited to anonymization, but supports conventional spatial queries as well. At the sametime, an adjusted median splits method is provided, aimed on effectiveness and efficiency.And a spatial k-anonymity algorithm based on locality-sensitive hashing partition isproposed. The algorithm is shown to preserve both locality and moderate computationcomplexity. It can also be used as splits method.
Secondly, a general model for privacy-aware mobile services over road networks(StarGCloaking) is proposed. StarGCloaking has three distinct features: it supports road-network-specific, personalized privacy and quality of service (QoS) requirements ona per request basis; it strikes a balance between the attack resilience of the performedprotection and the processing cost of the anonymous query; it scales to support a largenumber of mobile users with varying service requirements, through a star-graph basedprivatization model, powered by multi-folded optimizations in implementation.
Thirdly, an HSGCloaking algorithm to protect users’ privacy in road network isproposed. It orders the nodes of a star network by using Hilbert order to meet thereciprocity condition of every user. The cloaking framework supports k-nearest neighbor(k-NN) and range queries by presenting two query processing algorithms.
Finally, the correctness and validity of the above algorithms are proved by thetheoretical analysis and experimental verification.
引文
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