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Una tecnica efficiente per rendere sicuro l’accesso ai dati con la tecnica del Multi Overlapping Slicing

Una tecnica efficiente per rendere sicuro l’accesso ai dati con la tecnica del Multi Overlapping Slicing

Rani Ingawale / Somnath Thigale

54,12 €
IVA incluido
Disponible
Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Organización y gestión educativa
ISBN:
9786207616251
54,12 €
IVA incluido
Disponible

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Il Data Mining è il processo di analisi dei dati da diverse prospettive, di sintesi e di estrazione delle informazioni necessarie dal database. La maggior parte delle aziende raccoglie e archivia dati in grandi database. La privacy dei database è un’importante responsabilità delle organizzazioni, che devono proteggere le informazioni sensibili dei clienti perché si fidano di loro. Sono state proposte diverse tecniche di anonimizzazione per la privacy dei microdati sensibili. La generalizzazione perde una quantità considerevole di informazioni, soprattutto per i dati ad alta dimensionalità. La secchizzazione non impedisce la divulgazione dell’appartenenza e non si applica ai dati che non presentano una chiara separazione tra attributi quasi identificativi e attributi sensibili. Lo slicing è una tecnica proposta per anonimizzare i set di dati pubblicati, partizionando il set di dati verticalmente e orizzontalmente. La tecnica proposta aumenta l’utilità e la privacy di un set di dati suddiviso in fette, consentendo la sovrapposizione di fette, pur mantenendo la prevenzione della divulgazione dell’appartenenza. Inoltre, fornisce un accesso sicuro ai dati per più domini. Questo nuovo approccio lavora sull’overlapped slicing per migliorare e preservare l’utilità dei dati e la privacy meglio dell’slicing tradizionale.

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