VBTree: forward secure conjunctive queries over encrypted data for cloud computing

Wu, Zhiqiang; Li, Kenli

doi:10.1007/s00778-018-0517-6

Cited by 33 publications

(44 citation statements)

References 30 publications

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“…First, the existing tree-based Boolean/conjunctive query SSE schemes suffer from a logarithmic search overhead. Take IBTree [30] and VBTree [23] [41] for exam-ple. The u-dimensional conjunctive query complexity is O(u min w∈ϕ |DB(w)| log 2 n), where n is the total number of files, and ϕ is a u-dimensional conjunctive query.…”

Section: B Limitation Of Prior Artmentioning

confidence: 99%

“…Despite additional communication overhead and interactive rounds induced, hardware enclave based technique proposed in [45] will mitigate these problems. [10] O(mn) O(ux log n) -(SP, AP ) 1 IBTree [30] O(cn log n) O(ux log n) -(SP, AP ) 1 VBTree [23] O(N log n) O(ux log n) O(uvy log n)…”

Section: Proposed Approachmentioning

confidence: 99%

“…Later, the researchers used pseudo-random functions to achieve adaptive security, including the ones of [9] [46]. The first single-round zero-user-storage forward-private solution was proposed by Wu and Li in VLDBJ [23].…”

Section: Related Workmentioning

confidence: 99%

“…Current tree-based SSE works are capable of processing efficient conjunctive/Boolean queries, such as KRB in [10], Blindseer in [36], [42], PBTree in PVLDB '14 [12], IBTree in ICDE '17 [30], VBTree in VLDBJ '19 [23], etc. According to their designs, they can handle a conjunctive query on each tree node.…”

Section: Introductionmentioning

confidence: 99%

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Four-branch tree: highly efficient Boolean queries over encrypted cloud data

Wang

2024

IEEE Access

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This work aims to design highly efficient searchable encryption (SE) schemes to process Boolean queries over outsourced data files on untrusted public clouds while preserving users' privacy. Many tree-based SE schemes support sub-linear conjunctive queries. However, all the trees suffer from a logarithmic multiplicative overhead in each search process. To make the tree work as efficiently as possible, we present a novel tree data structure called four-branch tree (FBTree). Our core design is to make a tree node have four branches, which help the searching process to access the desired tree nodes quickly. FBTree acts as an efficient inverted index, but it is still a tree data structure. Based on this, two schemes are provided for different usage scenarios: one achieves nearly-optimal search complexity and strong adaptive security for the efficiency-first environment, and the other is a sub-linear Boolean-query scheme via Oblivious RAM for security-first settings. Several real datasets are used to evaluate FBTree performance. Testing results demonstrate that the FBTree structure has high efficiency and scalability for encrypted Boolean searches.

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Section: B Limitation Of Prior Artmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Four-branch tree: highly efficient Boolean queries over encrypted cloud data

Wang

2024

IEEE Access

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“…To achieve efficient conjunctive query process, [9] presented an unusual tree-based data arrangement called Virtual Binary (VB) tree. This method creates a tree totally kept in a hash table for effective updating and improved scalability.…”

Section: Related Workmentioning

confidence: 99%

Secure Ranked Multi-Keyword Search based on Modified Blowfish Algorithm and AVL Tree in Untrusted Cloud Environment

Swami,

Das

2019

IJEAT

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Advancement in cloud services growing day by day motivates a huge number of data proprietors to store their valuable data in cloud servers. For privacy issue, datasets that contain sensitive information are encrypted first and then outsourced into the cloud server. In this paper, ranked multi keyword search based on AVL tree, especially for several data owners, has been proposed. To avoid unauthorized access, the proposed work encrypts the data using a Modified Blowfish (MB) algorithm before outsourcing. MB algorithm introduces # operation instead of normal OR operation in conventional blowfish algorithm. This MB algorithm provides robustness against any intruding whereas the conventional blowfish algorithm insecure for many applications. To achieve a proficient search, every data owner’s index based on AVL tree is encrypted by way of additive order and the privacy-preserving family is formed. The cloud server is then permitted to combine these indexes effectually without knowing the index content. An Iterative Deepening Depth First Search (IDDFS) procedure is used to discover the matching file for the data user request. Finally, our proposed work provides secure data outsourcing to cloud server compared to the other existing methods. The proposed work considers three metrics for the performance evaluation process, viz. precision, index construction time and search time.

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Practical wildcard searchable encryption with tree‐based index

Zhang

Zhao

Qin

et al. 2021

Int J of Intelligent Sys

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Wildcard searchable encryption is an advanced variant of searchable encryption that can simultaneously maintain the searchability and confidentiality of the encrypted data. The wildcard searchable encryption outperforms the standard one for the fact that the users can use it to search the desired data even with the inexact keywords. Considering the millisecond level response time in the era of 5G, there are higher demands on the efficiency and accuracy that may be a pair of contradictions in wildcard searchable encryption. To improve the efficiency without sacrificing the accuracy, we put forward a novel scheme, tree-based index scheme (TBIS), through filtering the search results step by step instead of enumeration in the prior works and in the instantiation of TBIS, the search time drops sharply to the millisecond level. By using more kinds of characters, the accuracy of search result is improved visibly. TBIS achieves nonadaptive security that is indistinguishable against chosen character set attacks proposed in this paper. The security criteria can capture the relationship among characters, keywords and documents. At last, we put forward a frame structure in machine learning as an application of the proposed scheme.Abbreviations: IND-CCSA, indistinguishability against chosen character set attacks; TBIS, tree-based index scheme.

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VBTree: forward secure conjunctive queries over encrypted data for cloud computing

Cited by 33 publications

References 30 publications

Four-branch tree: highly efficient Boolean queries over encrypted cloud data

Four-branch tree: highly efficient Boolean queries over encrypted cloud data

Secure Ranked Multi-Keyword Search based on Modified Blowfish Algorithm and AVL Tree in Untrusted Cloud Environment

Practical wildcard searchable encryption with tree‐based index

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