PVSAE: A Public Verifiable Searchable Encryption Service Framework for Outsourced Encrypted Data

Searchable encryption allows a cloud server to conduct keyword search over encrypted data on behalf of the data users without learning the underlying plaintexts. However, most existing searchable encryption schemes only support single or conjunctive keyword search, while a few other schemes that can perform expressive keyword search are computationally inefficient since they are built from bilinear pairings over the composite-order groups. In this paper, we propose an expressive public-key searchable encryption scheme in the prime-order groups, which allows keyword search policies i.e., predicates, access structures to be expressed in conjunctive, disjunctive or any monotonic Boolean formulas and achieves significant performance improvement over existing schemes. We formally define its security and prove that it is selectively secure in the standard model. Also, we implement the proposed scheme using a rapid prototyping tool called Charm and conduct several experiments to evaluate it performance. The results demonstrate that our scheme is much more efficient than the ones built over the composite-order groups. INDEX TERMS - Searchable encryption, cloud computing, expressiveness, attribute-based encryption

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Aggregate Searchable Encryption With Result Privacy

Research Anthology on Artificial Intelligence Applications in Security ◽

10.4018/978-1-7998-7705-9.ch043 ◽

2021 ◽

pp. 922-945

Author(s):

Dhruti P. Sharma ◽

Devesh C. Jinwala

Keyword(s):

Data Analysis ◽

Count Data ◽

Data Extraction ◽

Searchable Encryption ◽

Primary Concern ◽

Conjunctive Query ◽

Encrypted Data ◽

Storage Server ◽

Partial Data ◽

Aggregate Query

With searchable encryption (SE), the user is allowed to extract partial data from stored ciphertexts from the storage server, based on a chosen query of keywords. A majority of the existing SE schemes support SQL search query, i.e. 'Select * where (list of keywords).' However, applications for encrypted data analysis often need to count data matched with a query, instead of data extraction. For such applications, the execution of SQL aggregate query, i.e. 'Count * where (list of keywords)' at server is essential. Additionally, in case of semi-honest server, privacy of aggregate result is of primary concern. In this article, the authors propose an aggregate searchable encryption with result privacy (ASE-RP) that includes ASearch() algorithm. The proposed ASearch() performs aggregate operation (i.e. Count *) on the implicitly searched ciphertexts (for the conjunctive query) and outputs an encrypted result. The server, due to encrypted form of aggregate result, would not be able to get actual count unless having a decryption key and hence ASearch() offers result privacy.

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Aggregate Searchable Encryption With Result Privacy

International Journal of Information Security and Privacy ◽

10.4018/ijisp.2020040104 ◽

2020 ◽

Vol 14 (2) ◽

pp. 62-82

Author(s):

Dhruti P. Sharma ◽

Devesh C. Jinwala

Keyword(s):

Count Data ◽

Data Extraction ◽

Searchable Encryption ◽

Primary Concern ◽

Conjunctive Query ◽

Search Query ◽

Encrypted Data ◽

Storage Server ◽

Partial Data ◽

Aggregate Query

With searchable encryption (SE), the user is allowed to extract partial data from stored ciphertexts from the storage server, based on a chosen query of keywords. A majority of the existing SE schemes support SQL search query, i.e. 'Select * where (list of keywords).' However, applications for encrypted data analysis often need to count data matched with a query, instead of data extraction. For such applications, the execution of SQL aggregate query, i.e. 'Count * where (list of keywords)' at server is essential. Additionally, in case of semi-honest server, privacy of aggregate result is of primary concern. In this article, the authors propose an aggregate searchable encryption with result privacy (ASE-RP) that includes ASearch() algorithm. The proposed ASearch() performs aggregate operation (i.e. Count *) on the implicitly searched ciphertexts (for the conjunctive query) and outputs an encrypted result. The server, due to encrypted form of aggregate result, would not be able to get actual count unless having a decryption key and hence ASearch() offers result privacy.

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Multiuser Searchable Encryption with Token Freshness Verification

Security and Communication Networks ◽

10.1155/2017/6435138 ◽

2017 ◽

Vol 2017 ◽

pp. 1-16 ◽

Cited By ~ 3

Author(s):

Dhruti Sharma ◽

Devesh C. Jinwala

Keyword(s):

Empirical Analysis ◽

Security Analysis ◽

Searchable Encryption ◽

Functional Encryption ◽

Search Query ◽

Search Activity ◽

Replay Attack ◽

Encrypted Data ◽

Practical Applications

A Multiuser Searchable Encryption (MUSE) can be defined with the notion of Functional Encryption (FE) where a user constructs a search token from a search key issued by an Enterprise Trusted Authority (ETA). In such scheme, a user possessing search key constructs search token at any time and consequently requests the server to search over encrypted data. Thus, an FE based MUSE scheme is not suitable for the applications where a log of search activities is maintained at the enterprise site to identify dishonest search query from any user. In addition, none of the existing searchable schemes provides security against token replay attack to avoid reuse of the same token. In this paper, therefore we propose an FE based scheme, Multiuser Searchable Encryption with Token Freshness Verification (MUSE-TFV). In MUSE-TFV, a user prepares one-time usable search token in cooperation with ETA and thus every search activity is logged at the enterprise site. Additionally, by verifying the freshness of a token, the server prevents reuse of the token. With formal security analysis, we prove the security of MUSE-TFV against chosen keyword attack and token replay attack. With theoretical and empirical analysis, we justify the effectiveness of MUSE-TFV in practical applications.

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Frequency-smoothing encryption: preventing snapshot attacks on deterministically encrypted data

IACR Transactions on Symmetric Cryptology ◽

10.46586/tosc.v2018.i1.277-313 ◽

2018 ◽

pp. 277-313 ◽

Cited By ~ 2

Author(s):

Marie-Sarah Lacharité ◽

Kenneth G. Paterson

Keyword(s):

Statistical Analysis ◽

Frequency Analysis ◽

Real Data ◽

Searchable Encryption ◽

Encrypted Data ◽

Attack Model ◽

Deterministic Encryption ◽

Classical Technique ◽

Inference Attacks ◽

Provably Secure

Statistical analysis of ciphertexts has been recently used to carry out devastating inference attacks on deterministic encryption (Naveed, Kamara, and Wright, CCS 2015), order-preserving/revealing encryption (Grubbs et al., S&P 2017), and searchable encryption (Pouliot and Wright, CCS 2016). At the heart of these inference attacks is classical frequency analysis. In this paper, we propose and evaluate another classical technique, homophonic encoding, as a means to combat these attacks. We introduce and develop the concept of frequency-smoothing encryption (FSE) which provably prevents inference attacks in the snapshot attack model, wherein the adversary obtains a static snapshot of the encrypted data, while preserving the ability to efficiently and privately make point queries. We provide provably secure constructions for FSE schemes, and we empirically assess their security for concrete parameters by evaluating them against real data. We show that frequency analysis attacks (and optimal generalisations of them for the FSE setting) no longer succeed.

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