A Credential Data Privacy Preserving in web Environment using Secure Data Contribution Retrieval Algorithm
Kumaran U, Neelu Khare
Journal of Intelligent Computing, Vol. 10, No. 3, 2019.
DOI: https://doi.org/10.6025/jic/2019/10/3/102-110
Link: http://www.dline.info/jic/fulltext/v10n3/jicv10n3_4.pdf
Abstract:
Preservation of privacy is a significant aspect of data mining and as the secrecy of sensitive information must be maintained while sharing the data among different untrusted parties. There are much application is suffering from vulnerable, data leakage, data misuse, and sensitive data disclosure issues. To protect the privacy of sensitive data without losing the usability of data, various techniques have been used in privacy-preserving data mining (PPDM). However, a system is unable to maintain the privacy during online services. Some of the approaches are available to maintain the tight privacy, but they fail to minimize the execution time and error rate. The main objective of the article is to contribute and retrieve the data with
minimal classification error and execution time with enhanced privacy. To overcome the issues, the paper introduces the Secure Data Contribution Retrieval algorithm to fulfill the current issues. Proposed algorithms define a privacy policy and arrange the security based on requirements. This design applies the privacy based on the compatibility of applications. This
approach computes the union of private multidatasets that each of the interacting with attributes and actors and another that tests the inclusion of an element held by one actor in a subset of another. It displays the table with hidden attributes in multiple categories wise for a user. This approach is capable of satisfying the accuracy constraints for multiple datasets. It also considers the efficient data extraction with a good ranking of attributes in tables. Based on experimental result proposed approach performs well regarding success rate, error rate and system execution time compare than existing methods.