Early warning systems for cyber defence
Data(s) |
2016
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Resumo |
<p>Cybercriminals ramp up their efforts with sophisticated techniques while defenders gradually update their typical security measures. Attackers often have a long-term interest in their targets. Due to a number of factors such as scale, architecture and nonproductive traffic however it makes difficult to detect them using typical intrusion detection techniques. Cyber early warning systems (CEWS) aim at alerting such attempts in their nascent stages using preliminary indicators. Design and implementation of such systems involves numerous research challenges such as generic set of indicators, intelligence gathering, uncertainty reasoning and information fusion. This paper discusses such challenges and presents the reader with compelling motivation. A carefully deployed empirical analysis using a real world attack scenario and a real network traffic capture is also presented.</p> |
Identificador |
http://dx.doi.org/10.1007/978-3-319-39028-4_3 http://www.scopus.com/inward/record.url?scp=84966605881&partnerID=8YFLogxK |
Idioma(s) |
eng |
Publicador |
Springer Verlag |
Direitos |
info:eu-repo/semantics/restrictedAccess |
Fonte |
Kalutarage , H , Shaikh , S , Lee , B S , Lee , C & Kiat , Y C 2016 , Early warning systems for cyber defence . in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . vol. 9591 , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 9591 , Springer Verlag , pp. 29-42 , IFIP WG 11.4 International Workshop on Open Problems in Network Security, iNetSec 2015 , Zurich , Switzerland , 29-29 October . DOI: 10.1007/978-3-319-39028-4_3 |
Palavras-Chave | #Bayesian inference #Cyber defence #Cyber warfare #Early warning systems #Future internet #/dk/atira/pure/subjectarea/asjc/1700 #Computer Science(all) #/dk/atira/pure/subjectarea/asjc/2600/2614 #Theoretical Computer Science |
Tipo |
contributionToPeriodical |