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.

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. Thisvolume, 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.

Contains revised, extended versions of papers selected from FDSE 2016 and ACOMP 2016 Includes indepth theoretical and applicational papers on data and security engineering Covers topics ranging from massive dataset mining to security and privacy Includes supplementary material: sn.pub/extras