臺灣博碩士論文加值系統

在雲計算時代，雲端伺服器扮演著舉足輕重的角色，除了能承載著繁重的計算任務。對於資料存儲來說，雲端伺服器能夠提供高效的資料存取方式。而對於資料隱私，很多雲端伺服器往往無法直接在傳統加密上進行工作。因此，加密資料的外包計算是雲端伺服器的隱私保護中一個急需解決的問題。在諸多文獻中，大量的密碼工具（同態加密、可搜索加密、等價測試加密）已經被用以解決部分雲端伺服器保護隱私和訪問加密資料的需求，而這些工具追求的是資料與檢索請求的完美匹配。與完美匹配相比，加密資料的相似度是一個更加靈活的概念。本文引入了用於加密資料的保有隱私外包相似度測驗（PPOS）來實現以下場景。雲對資料及其特徵向量進行加密，然後通過這些向量與檢索請求之間的相似度測驗來獲取目標資料。最近，Zhang等人提出了一種基於同態加密、亂碼電路和屬性加密的PPOS方案。而在本文中，我們致力於展示一個新的PPOS安全模型及其方案。首先，我們對PPOS面向半誠實攻擊者的安全性給出了嚴格的安全性定義。其次，我們希望盡可能減少對加密工具的密碼學難問題假設的使用。我們的解決方案是通過亂碼電路和屬性加密進行簡化，以避免使用同態加密。然而存在我們須克服的挑戰是，不能直接應用亂碼電路的安全性來證明所提出的方案的安全性。最終，我們將亂碼電路解釋為是由可選擇雙重加密（Chosen Double Encryption）所構成的組件，然後利用可選擇雙重加密的安全性來完成安全性證明。

In the era of cloud computing, the cloud server always plays a significant role to carry the heavy tasks of computation. As for storage services, it provides an efficient way to accessing data. For data privacy, encryption is usually referred to as the simple approach, but in fact cloud services cannot work with the traditional encryption. However, outsourced computing over encrypted data receives a lot attention of preserving privacy in the cloud setting. In the literature, lots of cryptographic primitives (i.e., homomorphic encryption, searchable encryption, encryption with equality test) have tackled a few cloud applications for preserving privacy and accessing encrypted data, and those require perfect match with query and data. A relaxed notion comparing with perfect match is similarity over encrypted data. Privacy-preserving outsourced similarity test (PPOS) over encrypted data is introduced to satisfy the following scenario. The cloud stores encrypted data with the encrypted feature vector, and then picks up the target data by testing similarity between those vectors and the search query. Recently, Zhang et al. proposed a PPOS scheme based on additive homomorphic encryption, garbled circuits, and ciphertext-policy attribute based encryption. In this thesis, we aim for presenting the formal security model and new scheme of PPOS. At first, we provide a formal definition to capture simulation security for PPOS against the semi-honest adversary. Secondly, we would like to use as few primitives as possible to minimize hardness assumptions in cryptography. Our solution is to avoid using homomorphic encryption to construct the proposed scheme simply from garbled circuits and ciphertext-policy attribute based encryption. However, there is a challenge that the security of garbled circuits cannot be directly applied to prove the security of the proposed scheme. Finally, we decouple the garbled circuit into many components of chosen double encryption, and then complete the security proof by using the security of chosen double encryption.

1 Introduction 1
2 Preliminaries 6
2.1 Garbled Circuits . . . . . . . . . . . . . . . . . . . . 6
2.2 Ciphertext Policy Attribute Based Encryption . . . . . . 7
2.3 Chosen Double Encryption . . . . . . . . . . . . . . . . 8
3 System Framework 11
3.1 Functionality . . . . . . . . . . . . . . . . . . . . . .11
3.2 New Security Model . . . . . . . . . . . . . . . . . . . 13
4 The Proposed Scheme 16
4.1 Processes . . . . . . . . . . . . . . . . . . . . . . . .16
4.2 Security Proof . . . . . . . . . . . . . . . . . . . . . 18
4.2.1 Building the Simulator . . . . . . . . . . . . . . . . 18
4.2.2 Proof Sketch . . . . . . . . . . . . . . . . . . . . . 19
4.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . 21
5 Conclusion 23
A Missing details of the security proof 24
B Homomorphic encryption 30
C PPOS scheme of Zhang 31
References 33

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