Isbn: 9786207457243 - an efficient technique to secure data access multi overlapping slicing: an efficient technique to secure data access for multiple domains using overlapping slicing (6 risultati)

Taschenbuch. Condizione: Neu. An Efficient Technique to Secure Data Access Multi Overlapping Slicing | An Efficient Technique to Secure Data Access for Multiple Domains Using Overlapping Slicing | Rani Ingawale (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207457243 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 responsi.…

Taschenbuch. Condizione: Neu. 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.…