
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVI
Special Issue on Data and Security Engineering
Springer (Publisher)
Published on 7. December 2017
Book
Paperback/Softback
XI, 193 pages
978-3-662-56265-9 (ISBN)
Description
This volume, the 36th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised, extended papers selected from the 3rd International Conference on Future Data and Security Engineering, FDSE 2016, and the 10th International Conference on Advanced Computing and Applications, ACOMP 2016, which were held in Can Tho City, Vietnam, in November 2016. Topics covered include big data analytics, massive dataset mining, security and privacy, cryptography, access control, deep learning, crowd sourcing, database watermarking, and query processing and optimization.
More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Illustrations
60 s/w Abbildungen
XI, 193 p. 60 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
324 gr
ISBN-13
978-3-662-56265-9 (9783662562659)
DOI
10.1007/978-3-662-56266-6
Schweitzer Classification
Other editions
Additional editions

Abdelkader Hameurlain | Josef Küng | Roland Wagner
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVI
Special Issue on Data and Security Engineering
E-Book
11/2017
Springer
€53.49
Available for download
Persons
Content
Risk-Based Privacy-Aware Access Control for Threat Detection Systems.- Systematic Digital Signing in Estonian e-Government Processes: Influencing Factors, Technologies, Change Management.- Towards a Fine-Grained Privacy-Enabled Attribute-Based Access Control Mechanism.- One-Class Collective Anomaly Detection Based on LSTM-RNNs.- Multihop Wireless Access Networks for Flood Mitigation Crowd-Sourcing Systems.- Assessment of Aviation Security Risk Management for Airline Turnaround Processes.- Scalable Automated Analysis of Access Control and Privacy Policies.- Partitioning-Insensitive Watermarking Approach for Distributed Relational Databases.