Secure ranked fuzzy multi-keyword search over outsourced encrypted cloud data

Khan, Neelam; Krishna, C. Rama; Khurana, Anu

doi:10.1109/iccct.2014.7001499

Cited by 20 publications

(3 citation statements)

References 22 publications

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“…In this paper, we assume that both data owner and end-users are trusted whereas the cloud server is semi-trusted, which is consistent to the previous works. 25,50,[84][85][86][87][88][89][90][91] By semi-trusted it means that the cloud server performs search task honestly but may try to extract confidential information from the encrypted documents, encrypted cluster index, encrypted document index and encrypted search queries.…”

Section: Cloud Server (Cs)mentioning

confidence: 99%

Document clustering for efficient and secure information retrieval from cloud

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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Summary Organizations prefer using cloud for storing their data due to availability of cost‐effective storage. The outsourced data include sensitive information, so data is encrypted as maintaining confidentiality and privacy of the documents is of paramount importance. Retrieving the desired information from the cloud requires efficient searching, which involves submission of search query to the cloud server by the end‐user. As the search terms may include sensitive information of an organization, it is desired that the search query should not reveal any confidential information. The existing works are not suitable for big‐data scenario due to high search time required for large document collections, thereby leading to increased cloud usage cost. Thus, an efficient approach to perform search on encrypted data using clustering is proposed in this paper. As the proposed technique clusters the documents based on the relationship between the keywords, the search method involves searching documents within the relevant cluster in contrast to searching the entire dataset. An efficient ranking method is incorporated to rank the documents according to the relevance to search query using Term Frequency‐Inverse Document Frequency (tf‐idf) value of the keywords in the documents, which leads to reduced communication overheads due to reduction in unnecessary documents being downloaded. Moreover, an efficient query randomization approach is proposed so that two or more queries involving the same search terms appear distinct. Experimental results using real datasets demonstrate that our proposed multi‐keyword ranked search scheme on encrypted cloud data significantly reduce the number of comparisons and search time in comparison to the existing techniques while maintaining recall of 100% and precision of 82%.

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Section: Cloud Server (Cs)mentioning

confidence: 99%

Document clustering for efficient and secure information retrieval from cloud

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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“…Some of the fuzzy schemes do not facilitate ranking and/or are based on deterministic trapdoors e.g. [6] [7] [8] [9] [10]. Therefore, the aim of this research is to explore the problem of fuzzy searching and propose novel, practical and efficient solutions to perform fuzzy Searchable Encryption while preserving the privacy.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy keywords enabled ranked searchable encryption scheme for a public Cloud environment

Tahir

Ruj

Sajjad

et al. 2019

Computer Communications

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Searchable Encryption allows a user or organization to outsource their encrypted documents to a Cloudbased storage service, while maintaining the ability to perform keyword searches over the encrypted text. However, most of the existing search schemes do not take the almost certain presence of typographical errors in the documents under consideration, when trying to obtain meaningful and accurate results. This paper presents a novel ranked searchable encryption scheme that addresses this issue by supporting fuzzy keywords. The proposed construction is based on probabilistic trapdoors that help resist distinguishability attacks. This paper for the first time proposes Searchable Encryption as a Service (SEaaS). The proposed construction is deployed on the British Telecommunication's public Cloud architecture and evaluated over a real-life speech corpus. Our security analysis yields that the construction satisfies strong security guarantees and is also quiet lightweight, by analyzing its performance over the speech corpus.

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“…Multi-keyword search over encrypted and outsourced data is explored in [5] but it lacks privacy preserving concept. In the same fashion, Khan et al [18] proposed a ranked multi-keyword search with fuzzy logic enhancing user experience in search process. It could minimize overhead when compared to the state of the art.…”

Section: Introductionmentioning

confidence: 99%

A Light Weight Cryptographic Technique for Secure Outsourcing and Retrieval of Data in Cloud Computing

Ramesh¹,

RAMA²

2019

IJITEE

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Outsourcing large volumes of data to public cloud has the potential benefits to consumers. It also brings security issues as the cloud is treated as untrusted from the user point of view. Security issues may arise due to many reasons such as virtualization, resource pooling, elasticity, hidden hardware problems besides internal and external attacks launched by adversaries. Service Level Agreements (SLAs) between Cloud Service Provider (CSP) and cloud consumer are to be honoured for better social welfare. Therefore, it is indispensable to have mechanisms to ensure security to outsourced data when it is at rest and when it is in transit as well. Towards this end, many solutions came as found in the literature. However, most of the cryptographic methods employed were expensive. It is still an open challenge to develop light weight cryptographic methods for secure storage and retrieval or search for outsourced encrypted data. In this paper we proposed a methodology for light weight encryption which proved to be effective and suitable for cloud computing environments. An algorithm named Hybrid Lightweight Data Encryption (HLDE) is proposed and implemented. Empirical study is made on the same to validate our approach. The experimental results revealed that the proposed method is better than the state of the art in terms of high performance and strong security to outsourced data in cloud computing.

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Secure ranked fuzzy multi-keyword search over outsourced encrypted cloud data

Cited by 20 publications

References 22 publications

Document clustering for efficient and secure information retrieval from cloud

Document clustering for efficient and secure information retrieval from cloud

Fuzzy keywords enabled ranked searchable encryption scheme for a public Cloud environment

A Light Weight Cryptographic Technique for Secure Outsourcing and Retrieval of Data in Cloud Computing

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