Synopsis
The concern over privacy of personal and sensitive information has led to the implementation of several techniques for hiding, obfuscating, syntactic anonymity and encrypting sensitive information in databases. The requirement of preserving privacy as well as the usability of sensitive data has led to development of nearest neighborhood techniques. In this work we propose a method that expands the scope of perturbation in PPDM as multilevel and multikey trust in privacy preserving data mining. An analogical approach with measuring the identification attacks, diversity attacks and the problem addresses the challenge by properly correlating perturbation across copies of different trust levels and keys that are pertaining to the sub domain contexts of the databases. Our proposed framework is architecturally robust and defends the attacks to achieve the privacy goal. Our framework supports data providers to deliver different forms of data with different privacy levels based on the market demand.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
A.V. Sriharsha, is B.Tech from Computer Science & Engineering from Andhra University and M.Tech from Information Technology from Sathyabhama University, Chennai. Ph.D. from SCSVMV University, Kancheepuram. I am currently working as Professor in the Department of CSE, Sree Vidyanikethan Engineering College, A.Rangampet, Tirupati, A.P.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Résultats de recherche pour PPDM using Syntactic Anonymity on Sensitive Data
Image fournie par le vendeur
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing Jul 2017, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The concern over privacy of personal and sensitive information has led to the implementation of several techniques for hiding, obfuscating, syntactic anonymity and encrypting sensitive information in databases. The requirement of preserving privacy as well as the usability of sensitive data has led to development of nearest neighborhood techniques. In this work we propose a method that expands the scope of perturbation in PPDM as multilevel and multikey trust in privacy preserving data mining. An analogical approach with measuring the identification attacks, diversity attacks and the problem addresses the challenge by properly correlating perturbation across copies of different trust levels and keys that are pertaining to the sub domain contexts of the databases. Our proposed framework is architecturally robust and defends the attacks to achieve the privacy goal. Our framework supports data providers to deliver different forms of data with different privacy levels based on the market demand. 140 pp. Englisch. N° de réf. du vendeur 9783330351301
Acheter neuf
EUR 55,90
Expédition à EUR 23
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sriharsha A. V.A.V. Sriharsha, is B.Tech from Computer Science & Engineering from Andhra University and M.Tech from Information Technology from Sathyabhama University, Chennai. Ph.D. from SCSVMV University, Kancheepuram. I am current. N° de réf. du vendeur 160063928
Acheter neuf
EUR 46,18
Expédition à EUR 48,99
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Paperback
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. N° de réf. du vendeur 3330351306
Acheter neuf
EUR 99,88
Expédition à EUR 11,58
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing Jul 2017, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The concern over privacy of personal and sensitive information has led to the implementation of several techniques for hiding, obfuscating, syntactic anonymity and encrypting sensitive information in databases. The requirement of preserving privacy as well as the usability of sensitive data has led to development of nearest neighborhood techniques. In this work we propose a method that expands the scope of perturbation in PPDM as multilevel and multikey trust in privacy preserving data mining. An analogical approach with measuring the identification attacks, diversity attacks and the problem addresses the challenge by properly correlating perturbation across copies of different trust levels and keys that are pertaining to the sub domain contexts of the databases. Our proposed framework is architecturally robust and defends the attacks to achieve the privacy goal. Our framework supports data providers to deliver different forms of data with different privacy levels based on the market demand.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. N° de réf. du vendeur 9783330351301
Acheter neuf
EUR 55,90
Expédition à EUR 60
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The concern over privacy of personal and sensitive information has led to the implementation of several techniques for hiding, obfuscating, syntactic anonymity and encrypting sensitive information in databases. The requirement of preserving privacy as well as the usability of sensitive data has led to development of nearest neighborhood techniques. In this work we propose a method that expands the scope of perturbation in PPDM as multilevel and multikey trust in privacy preserving data mining. An analogical approach with measuring the identification attacks, diversity attacks and the problem addresses the challenge by properly correlating perturbation across copies of different trust levels and keys that are pertaining to the sub domain contexts of the databases. Our proposed framework is architecturally robust and defends the attacks to achieve the privacy goal. Our framework supports data providers to deliver different forms of data with different privacy levels based on the market demand. N° de réf. du vendeur 9783330351301
Acheter neuf
EUR 55,90
Expédition à EUR 61,14
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
PPDM using Syntactic Anonymity on Sensitive Data
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330351306
ISBN 13 : 9783330351301
Neuf
Taschenbuch
Vendeur : preigu, Osnabrück, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. PPDM using Syntactic Anonymity on Sensitive Data | A. V. Sriharsha (u. a.) | Taschenbuch | 140 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330351301 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 109610663
Acheter neuf
EUR 48,60
Expédition à EUR 70
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 5 disponible(s)