Total views : 119
Modified Data Duplication Algorithm to Minimize the Redudancy of Data in Medical Database
Objective: To secure and reduce the data duplication in medical databases using Modified Sliding and Windowing proposed method. Method: Here we proposed Modified Sliding and Windowing technique (MSW). It enables the users to command entry of outsourced information notwithstanding though the proprietorship changes progressively by misusing randomized merged encryption, secures possession aggregate key appropriation. This counteracts information spillage not exclusively to denied user despite the fact that they already possessed that information, additionally to a legit however inquisitive distributed storages servers. Findings/ Results: The MSW method gives higher Effectiveness and lesser delay for finding duplication. This method consumes less Memory and provide greater accuracy than the existing duplication algorithms. The comparison is done with NS2 (Network Simulator2) using different dataset. Hence this proposed research can be used to reduce the data duplication in advanced databases with lesser correlations and parameters. Application/ Improvements: Data duplication algorithm can be improved in future by adding more parameters with higher accuracy based on severe attacks in future.
Data-Mining, Duplication, Navie Bayes Classifier, Privacy Mechanism.
- Sanakal R, Jayakumari T. Prognosis of Diabetes Using Data mining Approach-Fuzzy C Means Clustering and Support Vector Machine. International Journal of Computer Trends and Technology. 2014 May; 11(2):98–9. Crossref
- Wang K, Chen R. Privacy-Preserving Data Publishing: A Survey of Recent Developments. ACM Computing Survey. 2010; 42(4):1–53. Crossref
- Rizvi S, Mendelzon A. Extending Query Rewriting Techniques for Fine-Grained Access Control. Proceeding ACM SIGMOD International Conference Management of Data, 2004. p. 551–62. Crossref
- Chaudhuri S, Sudarshan S. Fine Grained Authorization through Predicated Grants. Proceeding IEEE International Conference Data Engineering, 2007. p. 1174–83. Crossref
- Elmagarmid KA, Ipeirotis PG. Duplicate Record Detection: A Survey. IEEE Trans. ON Knowledge and Data Engineering. 2007 Jan; 19(1):1–16. Crossref
- Maddodi S, Girija AV. Data Deduplication Techniques and Analysis. 3rd International Conference on Emerging Trends in Engineering & Technology, 2010. p. 581–5. crossref
- Rohit A, Surajit C. Eliminating fuzzy duplicates in data warehouses. Proceedings of the 28th International Conference on Very Large Databases (VLDB), 2002. p. 586–97.
- Draisbach U, Naumann F. DuDe: The duplicate detection toolkit Proceedings. International Workshop on Quality in Databases (QDB). 2010. p. 1–7.
- Prakash M, Singaravel G. A new model for privacy preserving sensitive Data Mining. IEEE 3rd International Conference on Computing Communication & Networking Technologies (ICCCNT), 2012. p. 1–8. Crossref
- Elmisery AM, Huaiguo Fu. Privacy preserving distributed learning clustering of healthcare data using cryptography protocols. 34th Annual Computer Software and Applications Conference Workshops (COMPSACW), 2008. p. 140–5.
- Bloom BH. Space/time tradeoffs in hash coding with allowable errors. Communication ACM. 1970 Jul; 13(7):422–6. Crossref
- Lin MY, Hsueh SC. Apriori-based frequent item set mining algorithms on Map Reduce. Proceedings of the 6th international conference on ubiquitous information management and communication, 2012 Feb. p. 1–12
- Kolb L, Thor A, Rahm E. Dedoop: efficient deduplication with Hadoop. Proceedings of the VLDB Endowment. 2012; 5:1878–81. Crossref
- Dassarma A, Jain A, Machanavajjhala A, and Bohannon P. An automatic blocking mechanism for large-scale de-duplication tasks. Proceedings of the 21st ACM international conference on Information and knowledge management, 2012. p. 1055–64.
- Muthitacharoen A, Chen B, Mazieres D. A low-bandwidth network file system. ACM SIGOPS Operating System. 2001 Dec; 35(5):174–87. Crossref
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.