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Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud.

Munisamy SD, Chokkalingam A - ScientificWorldJournal (2015)

Bottom Line: While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data.In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization.The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

View Article: PubMed Central - PubMed

Affiliation: R.M.D Engineering College, R.S.M Nagar, Kavaraipettai, Chennai, Tamil Nadu 601206, India.

ABSTRACT
Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

No MeSH data available.


CreateWildCardFuzzyMultiKeywordSet(MKW[ ][ ],edit).
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alg7: CreateWildCardFuzzyMultiKeywordSet(MKW[ ][ ],edit).

Mentions: Data owner has MKW = {(mk11, mk12,…, mk1n), (mk21, mk22,…, mk2n),…, (mkn1, mkn2,…, mkkn)} a set of multiple keywords of K data files. Data owner creates storage efficient fuzzy multikeyword set FMKS = {(fmk11[], fmk12[],…, fmk1n[]), (fmk21[], fmk22[],…, fmk2n[]),…, (fmkk1[], fmkk2[],…, fmkkn[])} using wild card based technique with the predefined edit distance value. Data owner executes Algorithm 7 to form fuzzy multikeyword Set.


Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud.

Munisamy SD, Chokkalingam A - ScientificWorldJournal (2015)

CreateWildCardFuzzyMultiKeywordSet(MKW[ ][ ],edit).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4562092&req=5

alg7: CreateWildCardFuzzyMultiKeywordSet(MKW[ ][ ],edit).
Mentions: Data owner has MKW = {(mk11, mk12,…, mk1n), (mk21, mk22,…, mk2n),…, (mkn1, mkn2,…, mkkn)} a set of multiple keywords of K data files. Data owner creates storage efficient fuzzy multikeyword set FMKS = {(fmk11[], fmk12[],…, fmk1n[]), (fmk21[], fmk22[],…, fmk2n[]),…, (fmkk1[], fmkk2[],…, fmkkn[])} using wild card based technique with the predefined edit distance value. Data owner executes Algorithm 7 to form fuzzy multikeyword Set.

Bottom Line: While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data.In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization.The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

View Article: PubMed Central - PubMed

Affiliation: R.M.D Engineering College, R.S.M Nagar, Kavaraipettai, Chennai, Tamil Nadu 601206, India.

ABSTRACT
Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

No MeSH data available.