Implementation of Guilt Model with Data Watcher for Leakage System

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This book is beneficial for those researchers who are working on Database and data ware house and mining. This book is also beneficial for company. In every enterprise, data leakage is very serious problem faced by it. An owner of enterprise has given sensitive data to its employee but in most of the situation employee leak the data. That leak data found in unauthorized place such as on the web of comparator enterprise or on laptop of employee of comparator enterprise or the owner of comparators laptop. It is either observed or sometimes not observed by owner. Leak data may be source code or design specifications, price lists, intellectual property and copy rights data, trade secrets, forecasts and budgets. In this case the data leaked out it leaves the company goes in unprotected the influence of the corporation. This uncontrolled data leakage puts business in a backward position. To find the solution on this problem we develop two models. First, when any employee of enterprise access sensitive data without the consent of owner and the second model for assessing the guilt of agents. Guilt model are used to improve the probability of identifying guilty third parties.

Autorentext

Nitin P Jagtap, Assistant Professor in Information Techonology Department at Shrama Sadhana Bombay Trust's College of Engineering and Technology, Jalgaon (India). Areas of interest are Database, Data Mining&Dataware,ERP Modules,Embedded Syte. Five research papers and one textbooks are on his credit.5.3 years professional Experience

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Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659293740
    • Sprache Englisch
    • Größe H220mm x B220mm x T150mm
    • Jahr 2012
    • EAN 9783659293740
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-659-29374-0
    • Titel Implementation of Guilt Model with Data Watcher for Leakage System
    • Autor Nitin Jagtap
    • Untertitel Identify Guilty Agent for Data Leakage Detection
    • Herausgeber LAP Lambert Academic Publishing
    • Anzahl Seiten 112
    • Genre Informatik

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