雷欽隆臺灣大學:電機工程學研究所周子超Chou, Tzu-ChowTzu-ChowChou2010-07-012018-07-062010-07-012018-07-062009U0001-2407200915134900http://ntur.lib.ntu.edu.tw//handle/246246/188150自從適地性服務被提出之後，地點隱私保護的機制也被廣泛地研究。然而大多數的機制因為像是使用錯誤的假設、提高伺服器負擔或降低服務品質等原因，並沒法辦法真正的實作出來。SpaceTwist[1]是一個原創且有效率的地點隱私保護的模型。根基於它的概念，在這篇論文中我們進一步地提出效率更高並且同時花費更低的地點隱私保護模型。其中主要的差別在於，(i)在用戶端的演算法中新增一條終止的條件，(ii)同步要求距離與網格邊長的S策略。我們使用來實際的資料庫來執行模擬，而其結果令人滿意。Since location-based service (LBS) was proposed, the location privacy protection schemes are wildly researched. However, because of many reasons such as making unrealistic assumption, incurring high server load or degrading quality of service, there are few schemes can be further practically implemented. A newly proposed location privacy protection scheme, named SpaceTwist [1], is novel as well as effective. Based on its concept, we propose an efficient way for location-based service privacy protection scheme in this thesis. The major differences are (i) maximum restriction termination condition in client-side algorithm and (ii) S-strategy for setting proper query distance and cell extent. We run our simulation in real POI (Point of Interest) datasets derived from Google local search API (Application Programming Interface) and the results is desirable.Chapter 1 Introduction................................1.1 Location Privacy Threat and Protection............1.2 Contributions of Our Scheme.......................3hapter 2 Related Works...............................4.1 K-anonymity.......................................4.2 Dummies Generation................................7.3 Obfuscation.......................................8.4 Cryptography-based................................9hapter 3 SpaceTwist Model...........................10.1 Overview.........................................10.2 Characteristics of SpaceTwist Model..............11.3 Client-side Query Processing Algorithm...........12.4 Server-side Granular Search Algorithm............13hapter 4 Our LBS Privacy Protection Scheme..........15.1 Maximum Restriction..............................15.2 S-Strategy.......................................16.3 Privacy Analysis.................................19hapter 5 Simulation.................................22.1 POI Datasets.....................................22.2 Environment of Simulation........................25.3 Simulation.......................................26.3.1 Influence of Query Distance....................26.3.2 Applying S-strategy............................28.3.3 Maximum restriction............................32.3.4 Applying S*-strategy...........................34hapter 6 Conclusion.................................37eferences...........................................383635634 bytesapplication/pdfen-US適地性服務地點隱私隱私保護location-based serviceLBSlocation privacyprivacy protectionthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/188150/1/ntu-98-R96921066-1.pdf