A hierarchical clustering method for big data oriented ciphertext search

Chen, Chi; Xiao-yan, Zhu; Shen, Peisong; Hu, Jiankun

doi:10.1109/infcomw.2014.6849292

Cited by 14 publications

(22 citation statements)

References 10 publications

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“…257 Hence, various researchers [27][28][29]43,50,55,70,75,[257][258][259] have incorporated the concept of result verification to searchable encryption. As an example, there may be a scenario where, during peak hours, the cloud server forwards incomplete or forged results to the end users.…”

Section: Support For Results Verificationmentioning

confidence: 99%

“…In the MRSE scheme 13 and its variants, 27,29,35,36,46,50,69,70,75,[80][81][82][83]93,107,[119][120][121]123,126 the query size is dependent on the number of keywords extracted from the document collection. In the MRSE scheme 13 and its variants, 27,29,35,36,46,50,69,70,75,[80][81][82][83]93,107,[119][120][121]123,126 the query size is dependent on the number of keywords extracted from the document collection.…”

Section: Rq4: How Is the Efficiency Of The Se Schemes Analyzed In Thementioning

confidence: 99%

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Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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Outsourcing confidential data to cloud storage leads to privacy challenges that can be reduced using encryption. However, with encryption in place, the utilization of the data is reduced, which leads to reduced quality of experience of the users. To overcome this, searchable encryption (SE) schemes are utilized, which allow the end users to retrieve the relevant documents from the cloud, for which various researchers have worked utilizing different techniques. Despite the popularity of the searchable encryption schemes, most of the surveys either do not provide or present an incomplete taxonomy of SE schemes. Hence, in this paper, we attempt to present a complete taxonomy/classification of the searchable encryption schemes in terms of the type of search, type of index, results retrieved, implementation type, multiplicity of users, and the technique used. From the literature, it is observed that inner product similarity is widely adopted by researchers to compute the similarity of the query and the document index as it provides both conjunctive and disjunctive searching (ie, have better search capability) but requires high search time (ie, have lower search efficiency). On the other hand, schemes based on binary comparisons exist, which require less search time (ie, have better search efficiency) but support only conjunctive searching (ie, have limited search capability). Thus, a major conclusion drawn from our work is that there is an imbalance between search capability and search efficiency, ie, in the existing schemes, search capability can be improved at the cost of search time only. Therefore, we suggest that one direction where researchers should work on is to provide a balance between search capability and search efficiency.

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Section: Support For Results Verificationmentioning

confidence: 99%

Section: Rq4: How Is the Efficiency Of The Se Schemes Analyzed In Thementioning

confidence: 99%

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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“…[2][3][4][5][6][7]. As shown in Fig.1, the proposed method is compared with existing solutions and has the advantage in maintaining the relationship between documents.…”

Section: Related Workmentioning

confidence: 99%

“…Thus, the orderpreserving strategies are applied to recognize the rank mechanism. Wang et al [3] use encrypted invert index to attain comfy ranked keyword seek over the encrypted files. In the quest segment, the cloud server computes the relevance rating among files and the question.…”

Section: Related Workmentioning

confidence: 99%

“…In this way, applicable documents are ranked in line with their relevance rating and customers can get the pinnacle-okay results. In the public key putting, Boneh et al [3] designed the primary searchable encryption production, wherein everybody can use the public key to jot down to the statistics stored on the server but most effective authorized users proudly owning private key can seek. However, all the above-mentioned strategies handiest support unmarried key-word search.…”

Section: Related Workmentioning

confidence: 99%

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A Script Towards Security-Preserving and Numerous Word Search Method on Encrypted Data in Cloud Computing Premises

2017

IJAERD

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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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A hierarchical clustering method for big data oriented ciphertext search

Cited by 14 publications

References 10 publications

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

A Script Towards Security-Preserving and Numerous Word Search Method on Encrypted Data in Cloud Computing Premises

Document clustering for efficient and secure information retrieval from cloud

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