An Efficient Technique to Secure Data Access Multi Overlapping Slicing

Language: English

Published by LAP LAMBERT Academic Publishing Jan 2024, 2024

6207457242 / 9786207457243

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This item is printed on demand - Print on Demand Titel. Neuware -Data Mining is the process of analyzing data from different perspectives, summarizing it, and extracting the needed information from the database. Most enterprises are collecting and storing data in large databases. Database privacy is an important responsibility of organizations to protect clients sensitive information because client trusts them to do so. Various anonymization techniques have been proposed for the privacy of sensitive microdata. Generalization loses a considerable amount of information, especially for high-dimensional data. Bucketization does not prevent membership disclosure and does not apply to data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. Slicing is a technique proposed for anonymized published datasets by partitioning the dataset vertically and horizontally. The proposed technique increases the utility and privacy of a sliced dataset by allowing overlapped slicing while maintaining the prevention of membership disclosure. It also provides secure data access for multiple domains. This novel approach works on overlapped slicing to improve, preserve data utility and privacy better traditional slicing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.…

Seller Inventory # 9786207457243

Title
An Efficient Technique to Secure Data Access Multi Overlapping Slicing
Author
Rani Ingawale
Publisher
LAP LAMBERT Academic Publishing Jan 2024
Publication year
2024
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6207457242
ISBN 13
9786207457243
Item weight
107 grams
Dimensions
220x150x4 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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