Title
Real Time Threat Prediction, Identification And Mitigation For Critical Infrastructure Protection Using Semantics, Event Processing And Sequential Analysis
Abstract
Seamless and faultless operational conditions of multi stakeholder Critical Infrastructures (CIs) are of high importance for today's societies on a global scale. Due to their population impact, attacks against their interconnected components can create serious damages and performance degradation which eventually can result in a societal crisis. Therefore it is crucial to effectively and timely protect these high performance - critical systems against any type of malicious cyber-physical intrusions. This can be realized by protecting CIs against threat consequences or by blocking threats to take place at an early stage and preventing further escalation or predicting threat occurrences and have the ability to rapidly react by eliminating its roots. In this paper a novel architecture is proposed in which these three ways of confronting with cyber - physical threats are combined using a novel semantics based risk methodology that relies on real time behavioral analysis. The final prototype provides the CI operator with a decision tool (DST) that imprints the proposed approach and which is capable of alerting on new unknown threats, generate suggestions of the required counter-actions and alert of probable threat existence. The implemented architecture has been tested and validated in a proof of concept scenario of an airport CI with simulated monitoring data.
Year
DOI
Venue
2013
10.1007/978-3-319-03964-0_12
CRITICAL INFORMATION INFRASTRUCTURES SECURITY, CRITIS 2013
Keywords
Field
DocType
Real Time Threat Detection, Critical Infrastructures, Semantics, Event Processing, Sequential Analysis, CUSUM Statistic
Population,Architecture,Damages,Stakeholder,Computer security,Computer science,Critical infrastructure protection,Complex event processing,Proof of concept,Semantics
Conference
Volume
ISSN
Citations 
8328
0302-9743
0
PageRank 
References 
Authors
0.34
8
5