DocumentCode :
3422778
Title :
Intelligent risk detection and analysis tools for critical infrastructure protection
Author :
Yasakethu, S.L.P. ; Jiang, Jianliang ; Graziano, A.
Author_Institution :
Dept. of Comput., Univ. of Surrey, Guildford, UK
fYear :
2013
fDate :
1-4 July 2013
Firstpage :
52
Lastpage :
59
Abstract :
The protection of the national infrastructures from cyber-attacks is one of the main issues for national and international security. In this article we describe a new European Framework-7 (FP7) funded research project, CockpicCI, and introduce intelligent rick detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable, Information and Communication Technology (ICT), while the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advance intrusion detection and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyber-attacks.
Keywords :
critical infrastructures; risk analysis; security of data; CI; CockpicCI; European framework-7 funded research project; FP7; ICT technologies; abnormal situations; critical infrastructure protection; cyber-attacks; field equipment; information and communication technology; intelligent risk analysis tools; intelligent risk detection; international security; intrusion detection; intrusion reaction tools; national infrastructures; national security; Critical infrastructures; Cyber-security; Intrusion detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
EUROCON, 2013 IEEE
Conference_Location :
Zagreb
Print_ISBN :
978-1-4673-2230-0
Type :
conf
DOI :
10.1109/EUROCON.2013.6624965
Filename :
6624965
Link To Document :
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