Multi-Keyword search over encrypted data with scoring and search pattern obfuscation

Abstract

Search over encrypted data recently became a critical operation that raised a considerable amount of interest in both academia and industry. Especially, as outsourcing, sensitive data to cloud prove to be a strong trend to benefit from the unmatched storage and computing capacities thereof. Indeed, privacy-preserving search over encrypted data, an apt term to address privacy-related issues concomitant in outsourcing sensitive data, have been widely investigated in the literature under different models and assumptions. In this work, we propose an efficient scheme that allows privacy-preserving search over encrypted data using queries with multiple keywords. Most important contributions of this work are as follows. Firstly, using a property referred as δ-mean query obfuscation, the proposed scheme hides the search patterns, which are allowed to leak in many works in the literature including our preliminary work on the subject Orencik et al. (2013) [1]. Secondly, a two-server setting is employed to eliminate the correlation between the queries and matching documents sent to the user under the A preliminary version of this work has been presented at IEEE CLOUD 2013 [1]. assumption that the two servers are not colluding. Thirdly, we propose a novel compression scheme that reduces both the communication cost between the two servers and the computation cost of the search operation more than 55 times compared to the standard approach. And finally, the proposed scheme also provides an effective scoring and ranking capability that is based on term frequency-inverse document frequency (tf-idf) weights of keyword-document pairs. Our analyses demonstrate that the proposed scheme is privacypreserving, efficient and effective.

A Searchable and Verifiable Data Protection Scheme for Scholarly Big Data

“…Cloud data secure searches are among the problems faced by users with the continuous development of cloud computing technology. A large number of researchers [34], [35], [36], [37], [38] have devoted efforts to proposing reliable schemes for secure searches of the data in the cloud.…”

“…Orencik et al [34] present a privacy-preserving searchable scheme for encrypted data using queries with multiple keywords. Additionally, the scheme can hide the search patterns and provide an effective scoring and ranking capability.…”

Password Authenticated Keyword Search

“…Using protocols for Searchable Encryption [1]- [4] clients with limited computing and storage resources can outsource encrypted data to a server or a collection of servers, perform search over the encrypted data (typically using encrypted keywords) and eventually retrieve searched data while preserving its privacy against the servers. Existing searchable encryption schemes can be broadly split into those where the keyword search procedure requires either high-entropy shared keys such as Symmetric Searchable Encryption (SSE) schemes from [3], [5], [6] or a private-public key pair such as Public Key Encryption with Keyword Search (PEKS) schemes from [1], [2], [6]- [10] on the user side.…”

“…Our direct PAKS construction follows conceptually the following more general approach that combines ideas behind Password Authenticated Secret Sharing (PASS) [11]- [17] and SSE [3], [5], [6]. In the registration phase, the user picks a password π and a high-entropy symmetric key K that will be used to encrypt keywords and secret-shares K protected with π across both servers.…”

MUSE: An Efficient and Accurate Verifiable Privacy-Preserving Multikeyword Text Search over Encrypted Cloud Data

“…If users cannot verify the completeness and correctness of search results, the upper-level decisions based on the search results may be misleading. Therefore, it is a challenge to research and give a searchable encryption scheme that supports verifiable privacy-preserving multikeyword text search over encrypted cloud data, which has become one of the hot issues in cloud computing recently [3][4][5][6][7][8].…”