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研究生:古佳怡
研究生(外文):Chia-Yi Ku
論文名稱:基於安全性的排名優化
論文名稱(外文):Ranking Optimization with Security Awareness
指導教授:鄭卜壬鄭卜壬引用關係
口試委員:曾新穆蔡銘峰張嘉惠陳信希
口試日期:2015-07-31
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:37
中文關鍵詞:安全性隱藏搜尋模式排名效能排名關聯度基於同儕
外文關鍵詞:securitysearch pattern privacyranking performancerank correlationpeer-based
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  隨著雲端儲存服務的普及,越來越多使用者選擇將資料儲存於雲端服務平台上(如:Dropbox、Google Drive、Apple iCloud Drive等),以方便後續管理與使用。然而,對於一些較隱私的資料,使用者儘管仍欲使用服務供應商所提供的儲存與管理服務,但因擔心可能遭受他人窺視、攻擊以及資料外洩的風險,而往往會傾向不將該類資料放於雲端平台上。因此,為提供使用者一個更好且安心的使用環境,許多雲端服務所需具備的隱私要求(privacy requirements)與相關加密與搜尋技術相繼被提出。其中一部分為有關搜尋模式(search pattern)的隱藏,即當使用者下達一組關鍵字查詢(query)後,對於最終回傳的排名結果(ranked list)應做適度隱藏。以避免雖已對查詢所下達的關鍵字做隱藏的動作,但因回傳的排名結果間的相似,而致第三方推測出兩筆查詢間有所關聯。並減少因洩漏使用者的行為模式或較常存取哪些特定文件等資訊,以使第三方有機會對此作特定攻擊。
  然而對於搜尋模式的隱藏,在現有辦法中皆存在著一些問題,如未考慮排名結果間次序性的重要度,搜尋模式隱藏時未對排名結果的效能做維持,或者耗費過多時間做隱藏等。為此,我們基於文件與查詢字眼間所計算出的相關分數(relevance score),提出同儕的概念。在維持排名結果品質的情況下,讓同一組的關鍵字查詢盡可能產生不同回傳結果,以隱藏使用者的搜尋行為。


Since cloud service are wide-spread used nowadays, more and more users store their data on cloud storage (e.g., Dropbox, Google Drive, Apple iCloud Drive, etc.) for management. However, because of the risks of information leakage, user might tend not to store sensitive personal data in cloud. Thus some privacy requirements and corresponding technologies are being proposed. One of the requirements is search pattern privacy (i.e., hiding the query search’s result). To avoid a third party infer query correlation from result correlation (i.e., similar query results might come from similar queries). And preventing focused attack because of private interest leakage.
Unfortunately, existing search pattern hiding techniques have some shortcomings. For example, the method does not consider rank order, do not maintain ranking performance, or is inefficient. Thus, based on the relevance score between document and query keyword, we propose the concept of peer. Not only to generate as different result as possible by the same query, but also maintain ranking performance. That means achieve search pattern privacy.

口試委員會審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT iv
目錄 v
圖目錄 vii
表目錄 viii
第一章 緒論……………………………………………………………………… 1
1.1 研究動機……………………………………………………………… 1
1.2 研究目的……………………………………………………………… 2
1.3 內容架構……………………………………………………………… 2
第二章 相關研究與文獻………………………………………………… 3
2.1 串流關聯度隱藏………………………………………………… 3
2.2 有條件限制的排名優化…………………………………… 3
2.3 增加無意義關鍵字的排名隱藏……………………… 3
2.4 Oblivious RAM…………………………………………… 4
第三章 研究方法………………………………………………………… 5
3.1 系統架構…………………………………………………………… 5
3.2 基本概念…………………………………………………………… 7
3.3 同儕切割…………………………………………………………… 9
3.4 基於同儕的交換方法……………………………………… 12
3.4.1 產生候選人………………………………………………………… 13
3.4.2 挑選適當者………………………………………………………… 18
3.5 使用者回饋機制………………………………………………… 20
第四章 實驗……………………………………………………………………… 23
4.1 實驗資料……………………………………………………………… 23
4.2 Baseline………………………………………………………… 23
4.3 評估方法……………………………………………………………… 23
4.4 實驗結果……………………………………………………………… 24
4.4.1 實驗一:與Baseline的比較………………………… 25
4.4.2 實驗二:第一個交換物件的策略比較…………… 27
4.4.3 實驗三:第二個交換物件的策略比較…………… 29
4.4.4 實驗四:搜尋結果間的關聯度變化………………… 31
4.4.5 實驗五:加入使用者回饋機制………………………… 33
第五章 結論與未來研究方向…………………………………………… 35
參考文獻………………………………………………………………………… 36

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[9] E. Stefanov, E. Shi, "Oblivistore: High performance oblivious cloud storage," in Security and Privacy, 2013 IEEE Symposium on, pp. 253-267, May 2013.
[10] E. Yilmaz, J. A. Aslam, and S. Robertson, "A new rank correlation coefficient for information retrieval," in Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 587-594, July 2008.
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