Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/533004
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Computer Science | |
dc.date.accessioned | 2023-12-26T05:22:10Z | - |
dc.date.available | 2023-12-26T05:22:10Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/533004 | - |
dc.description.abstract | The rapid adoption of cloud storage by enterprises has revolutionized data management practices, yet it has additionally presented challenges related to data security, storage efficiency, and redundancy. This research proposes novel methodologies to address these challenges and enhance and re-establish accomplishments in data deduplication, guaranteeing secure and efficient data management inside the cloud storage climate. At the enterprise level, the Secure Convergent Key Management Strategy (SCKMS) is presented, empowering secure tasks like looking through encrypted data, sharing data inside the enterprise, and downloading data from the cloud while limiting confidence in the cloud service provider (CSP). SCKMS integrates a proof of recuperation protocol that checks the realness of data proprietorship and a proof of possession protocol that permits clients to approve the honesty of their data against possibly malevolent CSPs. These protocols guarantee robust security and efficient data management inside the cloud. newline | |
dc.format.extent | Xxiii, 148p. | |
dc.language | English | |
dc.relation | 180 Nos. | |
dc.rights | university | |
dc.title | An Enhanced And Secured Data Deduplication Using Application Aware Local Global Source And Distributed Hash Table Based Load Balancing Approach For Optimized Cloud Storage Environment | |
dc.title.alternative | - | |
dc.creator.researcher | Usharani, S | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Theory and Methods | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | Bibliography p.149-169 | |
dc.contributor.guide | Kungumaraj, K | |
dc.publisher.place | Kodaikanal | |
dc.publisher.university | Mother Teresa Womens University | |
dc.publisher.institution | Department of Computer Science | |
dc.date.registered | 2015 | |
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | A4 | |
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 249.41 kB | Adobe PDF | View/Open |
02_preliminary pages.pdf | 809.63 kB | Adobe PDF | View/Open | |
03_contents.pdf | 314.37 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 147.51 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 1.1 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 569.97 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 524.27 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 790.43 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 859.99 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 550.16 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 155.27 kB | Adobe PDF | View/Open | |
12_chapter 8.pdf | 147.68 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 273.06 kB | Adobe PDF | View/Open |
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