SAP-SSE: Protecting Search Patterns and Access Patterns in Searchable Symmetric Encryption

2021 ◽  
Vol 16 ◽  
pp. 1795-1809
Author(s):  
Qiyang Song ◽  
Zhuotao Liu ◽  
Jiahao Cao ◽  
Kun Sun ◽  
Qi Li ◽  
...  
2015 ◽  
Vol 2015 (2) ◽  
pp. 263-281 ◽  
Author(s):  
Melissa Chase ◽  
Emily Shen

AbstractIn this paper, we consider a setting where a client wants to outsource storage of a large amount of private data and then perform substring search queries on the data – given a data string s and a search string p, find all occurrences of p as a substring of s. First, we formalize an encryption paradigm that we call queryable encryption, which generalizes searchable symmetric encryption (SSE) and structured encryption. Then, we construct a queryable encryption scheme for substring queries. Our construction uses suffix trees and achieves asymptotic efficiency comparable to that of unencrypted suffix trees. Encryption of a string of length n takes O(λn) time and produces a ciphertext of size O(λn), and querying for a substring of length m that occurs k times takes O(λm+k) time and three rounds of communication. Our security definition guarantees correctness of query results and privacy of data and queries against a malicious adversary. Following the line of work started by Curtmola et al. (ACM CCS 2006), in order to construct more efficient schemes we allow the query protocol to leak some limited information that is captured precisely in the definition. We prove security of our substring-searchable encryption scheme against malicious adversaries, where the query protocol leaks limited information about memory access patterns through the suffix tree of the encrypted string.


2021 ◽  
Author(s):  
Hong Liu ◽  
Xueqin Li ◽  
Erchuan Guo ◽  
Yunpeng Xiao ◽  
Tun Li

Abstract Dynamic searchable encryption methods allow a client to perform searches and updates over encrypted data stored in the cloud. However, existing researches show that the general dynamic searchable symmetric encryption (DSSE) scheme is vulnerable to statistical attacks due to the leakage of search patterns and access patterns, which is detrimental to protecting the users’ privacy. Although the traditional Oblivious Random Access Machine (ORAM) can hide the access pattern, it also incurs significant communication overhead and cannot hide the search pattern. These limitations make it difficult to deploy the ORAM method in real cloud environments. To overcome this limitation, a DSSE scheme called obliviously shuffled incidence matrix DSSE (OSM-DSSE) is proposed in this paper to access the encrypted data obliviously. The OSM-DSSE scheme realizes efficient search and update operations based on an incidence matrix. In particular, a shuffling algorithm using Paillier encryption is combined with 1-out-of-n obliviously transfer (OT) protocol and local differential privacy to obfuscate the search targets. Besides, a formalized security analysis and performance analysis on the proposed scheme is provided, which indicates that the OSM-DSSE scheme achieves high security, efficient searches, and low storage overhead. Also, this scheme not only completely hides the search and access patterns but also provides adaptive security against malicious attacks by adversaries. Furthermore, experimental results show that the OSM-DSSE scheme obtains 3-4x better execution efficiency than the state-of-art solutions.


2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yu Zhang ◽  
Yin Li ◽  
Yifan Wang

Searchable symmetric encryption that supports dynamic multikeyword ranked search (SSE-DMKRS) has been intensively studied during recent years. Such a scheme allows data users to dynamically update documents and retrieve the most wanted documents efficiently. Previous schemes suffer from high computational costs since the time and space complexities of these schemes are linear with the size of the dictionary generated from the dataset. In this paper, by utilizing a shallow neural network model called “Word2vec” together with a balanced binary tree structure, we propose a highly efficient SSE-DMKRS scheme. The “Word2vec” tool can effectively convert the documents and queries into a group of vectors whose dimensions are much smaller than the size of the dictionary. As a result, we can significantly reduce the related space and time cost. Moreover, with the use of the tree-based index, our scheme can achieve a sublinear search time and support dynamic operations like insertion and deletion. Both theoretical and experimental analyses demonstrate that the efficiency of our scheme surpasses any other schemes of the same kind, so that it has a wide application prospect in the real world.


2020 ◽  
Vol 17 (6) ◽  
pp. 1322-1332 ◽  
Author(s):  
Xueqiao Liu ◽  
Guomin Yang ◽  
Yi Mu ◽  
Robert H. Deng

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