In modern business process sometime sensitive data is distributed to set of supposedly trusted agents (third parties) by the owner of data. If in case distributed data where found at unauthorized place (e.g. on the website or somebody’s laptop) then the owner must be able to assess the likelihood that the leaked data come from one or more agents or not. Organizations mainly apply data or information security only in terms of network protection from intruders and hackers, but due to globalization and digitization there is rapid growth in the amount of sensitive data processing applications. In the organizations these data can be accessed from different medium which increases the chances of data leakage and trouble in guilt assessment. Data allocation strategy includes fake records in the distribution set along with sensitive data, it acts as watermark to identify the corresponding owner. If such sensitive information is leaked then with the help of fake records and distribution logic involvement of agent in the leakage can be traced. Suitable data allocation strategy improve's the probability of guilt detection and this reduces the catastrophic effect of data leakage.
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Rupesh Shrikant Mishra was born in Mumbai,India , he is son of Mrs. Shyama Mishra & Mr. Shrikant Mishra. In May 2007 he completed Bachelor of Computer Engineering and currently pursuing Masters degree in Computer Engineering from Terna Engineering College affiliated to The University of Mumbai,India.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In modern business process sometime sensitive data is distributed to set of supposedly trusted agents (third parties) by the owner of data. If in case distributed data where found at unauthorized place (e.g. on the website or somebody's laptop) then the owner must be able to assess the likelihood that the leaked data come from one or more agents or not. Organizations mainly apply data or information security only in terms of network protection from intruders and hackers, but due to globalization and digitization there is rapid growth in the amount of sensitive data processing applications. In the organizations these data can be accessed from different medium which increases the chances of data leakage and trouble in guilt assessment. Data allocation strategy includes fake records in the distribution set along with sensitive data, it acts as watermark to identify the corresponding owner. If such sensitive information is leaked then with the help of fake records and distribution logic involvement of agent in the leakage can be traced. Suitable data allocation strategy improve's the probability of guilt detection and this reduces the catastrophic effect of data leakage. 68 pp. Englisch. Bestandsnummer des Verkäufers 9783659417511
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mishra Rupesh S.Rupesh Shrikant Mishra was born in Mumbai,India , he is son of Mrs. Shyama Mishra & Mr. Shrikant Mishra. In May 2007 he completed Bachelor of Computer Engineering and currently pursuing Masters degree in Computer Engi. Bestandsnummer des Verkäufers 5154960
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In modern business process sometime sensitive data is distributed to set of supposedly trusted agents (third parties) by the owner of data. If in case distributed data where found at unauthorized place (e.g. on the website or somebody's laptop) then the owner must be able to assess the likelihood that the leaked data come from one or more agents or not. Organizations mainly apply data or information security only in terms of network protection from intruders and hackers, but due to globalization and digitization there is rapid growth in the amount of sensitive data processing applications. In the organizations these data can be accessed from different medium which increases the chances of data leakage and trouble in guilt assessment. Data allocation strategy includes fake records in the distribution set along with sensitive data, it acts as watermark to identify the corresponding owner. If such sensitive information is leaked then with the help of fake records and distribution logic involvement of agent in the leakage can be traced. Suitable data allocation strategy improve's the probability of guilt detection and this reduces the catastrophic effect of data leakage.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. Bestandsnummer des Verkäufers 9783659417511
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In modern business process sometime sensitive data is distributed to set of supposedly trusted agents (third parties) by the owner of data. If in case distributed data where found at unauthorized place (e.g. on the website or somebody's laptop) then the owner must be able to assess the likelihood that the leaked data come from one or more agents or not. Organizations mainly apply data or information security only in terms of network protection from intruders and hackers, but due to globalization and digitization there is rapid growth in the amount of sensitive data processing applications. In the organizations these data can be accessed from different medium which increases the chances of data leakage and trouble in guilt assessment. Data allocation strategy includes fake records in the distribution set along with sensitive data, it acts as watermark to identify the corresponding owner. If such sensitive information is leaked then with the help of fake records and distribution logic involvement of agent in the leakage can be traced. Suitable data allocation strategy improve's the probability of guilt detection and this reduces the catastrophic effect of data leakage. Bestandsnummer des Verkäufers 9783659417511
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Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Data Leakage Detection in Relational Database | Information Security | Rupesh S. Mishra (u. a.) | Taschenbuch | 68 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659417511 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 105592629
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