Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/307101
Title: Design and Evaluation of Data Security Technique to Preserve Confidentiality in Cloud Computing
Researcher: Deepak Garg
Guide(s): Shalli Rani
Keywords: Automation and Control Systems
Computer Science
Engineering and Technology
University: Chitkara University, Punjab
Completed Date: 2020
Abstract: newlineCloud computing has gained so much interest in very less span of time. it newlineis now a hot topic of research. Industries and academia have saved a lot of newlineefforts and money using cloud services. It is also an area of interest of the newlineattackers too. Attackers are applying new techniques to steal information newlineof industries and consumers from the cloud, also they are damaging or newlinecorrupting them. Cloud data security is a big challenge these days. As per newlinea report, 31% of the companies considered SaaS applications are less newlinesecured than their internal systems. In another report, it is expected that newlinethere will be a 44% increase in cloud expenditure by the end of the year. newlineCyber-Physical Systems (CPS) integrate the dynamics of the physical newlineprocesses with software and networking. CPS can be connected with cloud newlinecomputing as it provides low-cost storage resources and the flexibility of newlinecustomizing the environment according to the complex industrial newlineapplications. Among other challenges, Secure data access control is the newlinemost intimidating challenge in cloud-based CPS. To overcome these newlinechallenges, a Dynamic Hybrid Secure Encryption (DHSE) technique is newlineproposed, which combines three encryption schemes Advanced newlineEncryption Standard (AES), Identity-Based Encryption (IBE) and newlineAttribute-Based Encryption (ABE). The proposed scheme provides newlineconfidentiality with minimum encryption and decryption time. The newlineproposed work has three stages; data distribution, encryption, and data newlineretrieval. In data distribution, the input is pre-processed and divided into newlinecategories based upon the sensitivity of the data.
Pagination: 
URI: http://hdl.handle.net/10603/307101
Appears in Departments:Faculty of Computer Science

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1. title.pdfAttached File13.39 kBAdobe PDFView/Open
2. certificate.pdf93.45 kBAdobe PDFView/Open
3. preliminary pages.pdf106.28 kBAdobe PDFView/Open
4. abstract.pdf32.07 kBAdobe PDFView/Open
5. chapter 1.pdf1.06 MBAdobe PDFView/Open
5. chapter 2.pdf161.9 kBAdobe PDFView/Open
5. chapter 3.pdf539.61 kBAdobe PDFView/Open
5. chapter 4.pdf253.6 kBAdobe PDFView/Open
5. chapter 5.pdf521.68 kBAdobe PDFView/Open
5. chapter 6.pdf12.28 kBAdobe PDFView/Open
6. reference.pdf156.42 kBAdobe PDFView/Open
80_recommendation.pdf198.9 kBAdobe PDFView/Open
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