2,373 research outputs found
Efficient privacy preserving predicate encryption with fine-grained searchable capability for cloud storage
With the fast development in Cloud storage technologies and ever increasing use of Cloud data centres, data privacy and confidentiality has become a must. Indeed, Cloud data centres store each time more sensitive data such as personal data, organizational and enterprise data, transactional data, etc. However, achieving confidentiality with flexible searchable capability is a challenging issue. In this article, we show how to construct an efficient predicate encryption with fine-grained searchable capability. Predicate Encryption (PEPE) can achieve more sophisticated and flexible functionality compared with traditional public key encryption. We propose an efficient predicate encryption scheme by utilizing the dual system encryption technique, which can also be proved to be IND-AH-CPA (indistinguishable under chosen plain-text attack for attribute-hiding) secure without random oracle. We also carefully analyse the relationship between predicate encryption and searchable encryption. To that end, we introduce a new notion of Public-Key Encryption with Fine-grained Keyword Search (PEFKSPEFKS). Our results show that an IND-AH-CPA secure PE scheme can be used to construct an IND-PEFKS-CPA (indistinguishable under chosen plain-text attack for public-key encryption with fine-grained keyword search) secure PEFKSPEFKS scheme. A new transformation of PE-to-PEFKS is also proposed and used to construct an efficient PEFKSPEFKS scheme based on the transformation from the proposed PEPE scheme. Finally, we design a new framework for supporting privacy preserving predicate encryption with fine-grained searchable capability for Cloud storage. Compared to most prominent frameworks, our framework satisfies more features altogether and can serve as a basis for developing such frameworks for Cloud data centres.Peer ReviewedPostprint (author's final draft
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R-PEKS: RBAC Enabled PEKS for Secure Access of Cloud Data
In the recent past, few works have been done by combining attribute-based access control with multi-user PEKS, i.e., public key encryption with keyword search. Such attribute enabled searchable encryption is most suitable for applications where the changing of privileges is done once in a while. However, to date, no efficient and secure scheme is available in the literature that is suitable for these applications where changing privileges are done frequently. In this paper our contributions are twofold. Firstly, we propose a new PEKS scheme for string search, which, unlike the previous constructions, is free from bi-linear mapping and is efficient by 97% compared to PEKS for string search proposed by Ray et.al in TrustCom 2017. Secondly, we introduce role based access control (RBAC) to multi-user PEKS, where an arbitrary group of users can search and access the encrypted files depending upon roles. We termed this integrated scheme as R-PEKS. The efficiency of R-PEKS over the PEKS scheme is up to 90%. We provide formal security proofs for the different components of R-PEKS and validate these schemes using a commercial dataset
A Practical Searchable Symmetric Encryption Scheme for Smart Grid Data
Outsourcing data storage to the remote cloud can be an economical solution to
enhance data management in the smart grid ecosystem. To protect the privacy of
data, the utility company may choose to encrypt the data before uploading them
to the cloud. However, while encryption provides confidentiality to data, it
also sacrifices the data owners' ability to query a special segment in their
data. Searchable symmetric encryption is a technology that enables users to
store documents in ciphertext form while keeping the functionality to search
keywords in the documents. However, most state-of-the-art SSE algorithms are
only focusing on general document storage, which may become unsuitable for
smart grid applications. In this paper, we propose a simple, practical SSE
scheme that aims to protect the privacy of data generated in the smart grid.
Our scheme achieves high space complexity with small information disclosure
that was acceptable for practical smart grid application. We also implement a
prototype over the statistical data of advanced meter infrastructure to show
the effectiveness of our approach
State of The Art and Hot Aspects in Cloud Data Storage Security
Along with the evolution of cloud computing and cloud storage towards matu-
rity, researchers have analyzed an increasing range of cloud computing security
aspects, data security being an important topic in this area. In this paper, we
examine the state of the art in cloud storage security through an overview of
selected peer reviewed publications. We address the question of defining cloud
storage security and its different aspects, as well as enumerate the main vec-
tors of attack on cloud storage. The reviewed papers present techniques for key
management and controlled disclosure of encrypted data in cloud storage, while
novel ideas regarding secure operations on encrypted data and methods for pro-
tection of data in fully virtualized environments provide a glimpse of the toolbox
available for securing cloud storage. Finally, new challenges such as emergent
government regulation call for solutions to problems that did not receive enough
attention in earlier stages of cloud computing, such as for example geographical
location of data. The methods presented in the papers selected for this review
represent only a small fraction of the wide research effort within cloud storage
security. Nevertheless, they serve as an indication of the diversity of problems
that are being addressed
Privacy-Preserving Genetic Relatedness Test
An increasing number of individuals are turning to Direct-To-Consumer (DTC)
genetic testing to learn about their predisposition to diseases, traits, and/or
ancestry. DTC companies like 23andme and Ancestry.com have started to offer
popular and affordable ancestry and genealogy tests, with services allowing
users to find unknown relatives and long-distant cousins. Naturally, access and
possible dissemination of genetic data prompts serious privacy concerns, thus
motivating the need to design efficient primitives supporting private genetic
tests. In this paper, we present an effective protocol for privacy-preserving
genetic relatedness test (PPGRT), enabling a cloud server to run relatedness
tests on input an encrypted genetic database and a test facility's encrypted
genetic sample. We reduce the test to a data matching problem and perform it,
privately, using searchable encryption. Finally, a performance evaluation of
hamming distance based PP-GRT attests to the practicality of our proposals.Comment: A preliminary version of this paper appears in the Proceedings of the
3rd International Workshop on Genome Privacy and Security (GenoPri'16
Achieving Secure and Efficient Cloud Search Services: Cross-Lingual Multi-Keyword Rank Search over Encrypted Cloud Data
Multi-user multi-keyword ranked search scheme in arbitrary language is a
novel multi-keyword rank searchable encryption (MRSE) framework based on
Paillier Cryptosystem with Threshold Decryption (PCTD). Compared to previous
MRSE schemes constructed based on the k-nearest neighbor searcha-ble encryption
(KNN-SE) algorithm, it can mitigate some draw-backs and achieve better
performance in terms of functionality and efficiency. Additionally, it does not
require a predefined keyword set and support keywords in arbitrary languages.
However, due to the pattern of exact matching of keywords in the new MRSE
scheme, multilingual search is limited to each language and cannot be searched
across languages. In this pa-per, we propose a cross-lingual multi-keyword rank
search (CLRSE) scheme which eliminates the barrier of languages and achieves
semantic extension with using the Open Multilingual Wordnet. Our CLRSE scheme
also realizes intelligent and per-sonalized search through flexible keyword and
language prefer-ence settings. We evaluate the performance of our scheme in
terms of security, functionality, precision and efficiency, via extensive
experiments
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