Efficient Data Integrity Algorithm for Outsourced Data in Cloud Environment
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 3
Abstract
With The Rapid Advances In Communication Services And Increasing Growth In Outsourcing Of Data To Cloud Environment; Concerns Of Data Integrity Of Outsourced Data Is On The Rise. The Evidence Of Data Integrity Being Tampered And Up-To Date, Seem To Be Of Immediate Concern. Current Data Integrity Techniques Are Inefficient To Provide Fast User Data Verification Or To Check The Correctness Of Data Without Additional Storage Overhead At The Data Owner (DO). For Data Owners With Large Data Files, Existing Techniques Are Not Feasible Solutions. In This Paper, We Propose An Efficient Alternative Technique For The Integrity Of Outsourced Data Using Optimal Bloom Filters (OBF). We Propose The Basic Data Integrity Method And Discuss Various Alternatives To Design The Optimal Data Integrity Model. We Present A Detailed Analysis And Experimental Results For One Of The Alternative. These Results Are Compared With The Current Data Integrity Algorithms Such As SHA-1 And MD5. The Proposed Technique Using Bloom Filter Implementations Is Highly Space-Efficient At The Expense Of Extra Computational Overhead And The Multicore Implementations Have Significantly Reduced The Execution Time. The Presented Results Demonstrate That Employing Bloom Filters To Enforce Data Integrity For Outsourced Data In Cloud Environments Is Feasible And Efficient Than Traditional Techniques.
Authors and Affiliations
Pramod Kumar, MMS Rauthan, Vikram Kapoor
Keywords
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