%0 Conference Proceedings
%T Predicting and Preventing Insider Threat in Relational Database Systems
%+ Dept. of Computer Science and Computer Engineering
%A Yaseen, Qussai
%A Panda, Brajendra
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 4th IFIP WG 11.2 International Workshop on Information Security Theory and Practices: Security and Privacy of Pervasive Systems and Smart Devices (WISTP)
%C Passau, Germany
%Y Pierangela Samarati; Michael Tunstall; Joachim Posegga; Konstantinos Markantonakis; Damien Sauveron
%I Springer
%3 Information Security Theory and Practices. Security and Privacy of Pervasive Systems and Smart Devices
%V LNCS-6033
%P 368-383
%8 2010-04-12
%D 2010
%R 10.1007/978-3-642-12368-9_30
%K Relational Database
%K Security
%K Insider Threat
%K Dependencies
%Z Computer Science [cs]/Digital Libraries [cs.DL]Conference papers
%X This paper investigates the problem of insider threat in relational database systems. It defines various types of dependencies as well as constraints on dependencies that may be used by insiders to infer unauthorized information. Furthermore, it introduces the Constraint and Dependency Graph (CDG), and the Dependency Matrix that are used to represent dependencies and constraints on them. Furthermore, it presents an algorithm for constructing insiders knowledge graph, which shows the knowledgebase of insiders. In addition, the paper introduces the Threat Prediction Graph (TPG) to predict and prevent insider threat.
%G English
%2 https://inria.hal.science/hal-01056069/document
%2 https://inria.hal.science/hal-01056069/file/60330372.pdf
%L hal-01056069
%U https://inria.hal.science/hal-01056069
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-LNCS-6033
%~ IFIP-TC
%~ IFIP-TC11
%~ IFIP-WISTP
%~ IFIP-WG11-2
%~ IFIP-2010