My Account Log in

1 option

Privacy in Statistical Databases : UNESCO Chair in Data Privacy, International Conference, PSD 2016, Dubrovnik, Croatia, September 14-16, 2016, Proceedings / edited by Josep Domingo-Ferrer, Mirjana Pejić-Bach.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

View online
Format:
Book
Contributor:
Domingo-Ferrer, Josep, editor.
Pejić-Bach, Mirjana, editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 9867.
Information Systems and Applications, incl. Internet/Web, and HCI ; 9867
Language:
English
Subjects (All):
Application software.
Data mining.
Computer security.
Database management.
Data encryption (Computer science).
Computers and civilization.
Computer Appl. in Administrative Data Processing.
Data Mining and Knowledge Discovery.
Systems and Data Security.
Database Management.
Cryptology.
Computers and Society.
Local Subjects:
Computer Appl. in Administrative Data Processing.
Data Mining and Knowledge Discovery.
Systems and Data Security.
Database Management.
Cryptology.
Computers and Society.
Physical Description:
1 online resource (X, 273 pages) : 45 illustrations.
Edition:
First edition 2016.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2016.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2016, held in Dubrovnik, Croatia in September 2016 under the sponsorship of the UNESCO chair in Data Privacy. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The scope of the conference is on following topics: tabular data protection; microdata and big data masking; protection using privacy models; synthetic data; remote and cloud access; disclosure risk assessment; co-utile anonymization.
Contents:
Tabular Data Protection
Microdata and Big Data Masking
Protection Using Privacy Models
Synthetic Data
Remote and Cloud Access
Disclosure Risk Assessment
Co-utile Anonymization.
Other Format:
Printed edition:
ISBN:
978-3-319-45381-1
9783319453811
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account