An Efficient Technique to Secure Data Access for Multiple Domains using Overlapping Slicing

Abstract

Data Mining is the process of analysing data from different perspective, summarizing it into useful information and extracts the needed information from the database. Most enterprises are collecting and storing data in large database. Database privacy is a important responsibility of organizations for to protects clients sensitive information, because their clients trust them to do so. Various anonymization techniques have been proposed for the privacy of sensitive microdata. However, there is considered between the level of privacy and the usefulness of the published data. Recently, slicing was proposed as a technique for anonymized published dataset by partitioning the dataset vertically and horizontally. This paper proposes a technique to increase the utility and privacy of a sliced dataset by allowing overlapped slicing while maintaining the prevention of membership disclosure. Also provide secure data access for multiple domains. This novel approaches work on overlapped slicing to improve preserve data utility and privacy better than traditional slicing.
DOI: 10.17762/ijritcc2321-8169.160450