Cross-lingual multi-keyword rank search with semantic extension over encrypted data

Guan, Zhitao; Liu, Xueyan; Wu, Lina; Wu, Jun; Xu, Ran; Zhang, Jinhu; Li, Yuanzhang

doi:10.1016/j.ins.2019.11.013

Cited by 64 publications

(42 citation statements)

References 20 publications

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“…Unfortunately, OPE keeps the encrypted data sorted, which may cause leakage attack.the rank privacy are slightly weakened. In 2020, Guan et al [23] designed a Cross-lingual multi-keyword rank search with semantic extension, which also speed up the sorting process by designing a top-k data retrieval protocol based on the heap binary tree structures.…”

Section: B Ranked Searchable Encryptionmentioning

confidence: 99%

“…In terms of security, [23] uses a heuristics method to hide search patterns and access patterns, so its security analysis is not within the comparison scope. [14] builds the search index based on fully homomorphic encryption (LWE-Brakerski).…”

Section: Performance a Theoretical Analysismentioning

confidence: 99%

“…The above methods reach high security but lead to high computation or communication cost. [18] and [23] also use two non-collusion two-server setting to rank the search results, however, during the interaction between servers, one of the servers can access the plaintext of each search result, which leak the search and rank privacy. TS-RDSE encrypts the weight scores based on homomorphic encryption algorithm and the servers can calculate and compare the encrypted weights without decryption, so as to sort the search results without obtaining additional information.…”

Section: Performance a Theoretical Analysismentioning

confidence: 99%

“…What's more, many schemes did not take the keyword frequency into account, so the rank order of two files will be the same even if one contains all the searched keyword infrequently and the other one contains the same keyword very frequently. In terms of security, the proposed solutions are mainly based on higher assumptions [15], [19] (e.g., introducing trusted third parties) or specific security models [11], [18], [20]- [23] (e.g., the rank privacy are slightly weakened by allowing server obtain weight information).…”

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confidence: 99%

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An Efficient Two-Server Ranked Dynamic Searchable Encryption Scheme

Zhou

et al. 2020

IEEE Access

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Searchable encryption (SE) allows users to search over encrypted data without decrypting. In most existing SE schemes, server returns all matched files without relevance ranking, and the update mechanism are suffering with high communication and computation cost, which are not efficient enough to satisfy the real-life dynamic scenario. Addressing the above issues, we proposed TS-RDSE-a Two-Server Ranked Dynamic Searchable Encryption scheme. We integrate orthogonal vector and efficient homomorphic encryption cryptosystems to build a vector-level dynamic secure index, which simultaneously supports efficient dynamic update operations like deletion and insertion of files flexibly. Moreover, in order to rank the search results by relevance without decryption, we build a secure sorting protocol based on the widely-used tf-idf weighting formula and addition property of partial homomorphic encryption, which achieves accurate sorting for the search results while protecting the privacy of relevance scores. We give a comprehensive analysis of the correctness of TS-RDSE in the aspect of searching and sorting with mathematical proofs. The security analysis shows that TS-RDSE is secure against adaptive dynamic chosen-keyword attacks (CKA2) by honest-but-curious adversaries in random oracle model. The performance analysis shows that TS-RDSE has both a very light user workload and a moderate server workload, and it is superior to the existing approaches in terms of functionalities and expansibility. Extensive experiments on the real-world dataset validate our analysis and show that TS-RDSE is suitable for the real world cloud storage environment. INDEX TERMS Searchable encryption, dynamic update, homomorphic encryption, secure sorting. I. MOTIVATION The correctness of TS-RDSE implies that, for all security parameters k, all keys (K , SK , PK) generated by KeyGen(1 k), for all (γ , c) outputs by Setup(K , PK , f), and for all sequences of search or update operations on γ , Sort(S 1 (Search(S 1 (T okenGen(PK , K , W), γ); S 2 (SK)), PK); S 2 (SK)) will always outputs the correct ranked results R s , that is, not only satisfies the search request, but is sorted according to the corresponding weight scores. C. SECURITY DEFINITION The security definition for TS-RDSE is formalized by the four leakage functions L 1 , L 2 , L 3 and L 4 , which denote the information leaked to S 1 and S 2 in different phases.

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Section: B Ranked Searchable Encryptionmentioning

confidence: 99%

Section: Performance a Theoretical Analysismentioning

confidence: 99%

Section: Performance a Theoretical Analysismentioning

confidence: 99%

mentioning

confidence: 99%

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An Efficient Two-Server Ranked Dynamic Searchable Encryption Scheme

Zhou

et al. 2020

IEEE Access

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“…The common techniques on word embedding [24] or sentence embedding [25] include GloVe [26], PSL [27], ST [28], SCBOW [29], PROJ [30], PP-tf-idf [31], DAN [32], LSTM [33], and RNN [30]. The similarity in semantics can be applied to many NLP fields [34]- [36]. Z.-T. Guan et al proposed a cross-lingual multikeyword ranked search scheme based on the open multilingual WordNet with flexible keyword and language preference settings [34].…”

Section: B Sentence Similaritymentioning

confidence: 99%

A Quantum Entanglement-Based Approach for Computing Sentence Similarity

Qiu

Yan

2020

IEEE Access

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It is important to learn directly from original texts in natural language processing (NLP). Many deep learning (DP) models needing a large number of manually annotated data are not effective in deriving much information from corpora with few annotated labels. Existing methods using unlabeled language information to provide valuable messages consume considerable time and cost. Our provided sentence representation based on quantum computation (called Model I) needs no prior knowledge except word2vec. To reduce some semantic noise caused by the tensor product on the entangled words vector, two improved models (called Model II and Model III) are proposed to reduce the dimensions of the sentence embedding stimulated by Model I. The provided models are evaluated in the STS tasks of 2012, 2014, 2015 and 2016, for a total of 21 corpora. Experimental results show that using quantum entanglement and dimensionality reduction in sentence embedding yields state-of-the-art performances on semantic relations and syntactic structures. Compared to the Pearson correlation coefficient (Pcc) and mean squared error (MSE), the results of 16 out of 16 corpora are better than the results of the comparative methods.

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Topology hiding routing based on learning with errors

Wan

2020

Concurrency and Computation

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The protocol of onion routing constitutes the underpinning of Onion Routing network for anonymous communication. However, since the main idea behind such protocol is to hierarchically peel the IP head and decode each crypted routing address, the topology with regards to path length or long-term direction cannot be preserved. Owing to topology exposure, lots of attacks such as denial of service and differential flow analysis can be effectively conducted to violate the security of it. Moreover, considering that the path should be constructed by a sender in advance, onion routing is infeasible to be transplanted to ad hoc networks, let alone other defects such as heavy burden about computational complexity and package length. In this paper, a topology-hiding routing protocol is proposed to address most of the aforementioned problems recurring to homomorphic learning with errors. Security analysis illustrated that nothing but only the IPs of adjacent hops will be revealed to any router. Also the computational complexity on sender side as well as the package length outperforms those of traditional onion routing algorithm in view of comparative simulation. K E Y W O R D Slearning with errors, the onion routing, topology hiding onion routing INTRODUCTIONWithin the open and synergic environment of network, routing is undoubtedly the core for all its functionalities. Based on Dijkstra's algorithm, any package can be delivered to its destination through a shortest transmission path. Though plain routing is simple and efficient, it is vulnerable toward privacy infringement and various active attacks. For example, if the source and destination addresses are exposed to an adversary, he is not only capable of learning the relationship between the communication parties but may also locate their current position. In order to preserve the privacy related to IP addresses, an anonymous communication network named the Onion Routing (TOR) was first established by the U.S. NavalResearch Laboratory in the mid-1990s. 1 Aiming at concealing the start and the end addresses of communication to accomplish anonymity, TOR is realized via multilayer encryption manifested as an onion structure. Formally speaking, the idea behind TOR can be described as the following steps.1. The sender determines the route to the destination, presented as a sequencewhere R i stands for the IP address of intermediate routers. Then it encapsulates this route as R2 | R3 | … | Rn | D according a predefined public cryptosystem E PK (⋅) for Ri+1 = E PK i (R i+1 )and D = E PK n (D). As part of the IP package this information will be transmitted to the first router R 1 .2. Assuming that a router R i has received a message containing)to be aware of the next IP and relay the package till it arrives at the destination D.Although TOR is widely used to prevent messages from tracing in nowadays, a lot of defects such as timing analysis and exit node vulnerability remains unsolved. Besides, we argue some other weaknesses which may jeopardize its implementation and security as...

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Cross-lingual multi-keyword rank search with semantic extension over encrypted data

Cited by 64 publications

References 20 publications

An Efficient Two-Server Ranked Dynamic Searchable Encryption Scheme

An Efficient Two-Server Ranked Dynamic Searchable Encryption Scheme

A Quantum Entanglement-Based Approach for Computing Sentence Similarity

Topology hiding routing based on learning with errors

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