DocumentCode :
3276910
Title :
Risk analysis in cyber situation awareness using Bayesian approach
Author :
Bode, Moyinoluwa Abidemi ; Alese, Boniface Kayode ; Oluwadare, Samuel Adebayo ; Thompson, Aderonke Favour-Bethy
Author_Institution :
Dept. of Planning/ICT, Eng. Mater. Dev. Inst., Akure, Nigeria
fYear :
2015
fDate :
8-9 June 2015
Firstpage :
1
Lastpage :
12
Abstract :
The unpredictable cyber attackers and threats have to be detected in order to determine the outcome of risk in a network environment. This work develops a Bayesian network classifier to analyse the network traffic in a cyber situation. It is a tool that aids reasoning under uncertainty to determine certainty. It further analyze the level of risk using a modified risk matrix criteria. The classifier developed was experimented with various records extracted from the KDD Cup´99 dataset with 490,021 records. The evaluations showed that the Bayesian Network classifier is a suitable model which resulted in same performance level for classifying the Denial of Service (DoS) attacks with Association Rule Mining while as well as Genetic Algorithm, the Bayesian Network classifier performed better in classifying probe and User to Root (U2R) attacks and classified DoS equally. The result of the classification showed that Bayesian network classifier is a classification model that thrives well in network security. Also, the level of risk analysed from the adapted risk matrix showed that DoS attack has the most frequent occurrence and falls in the generally unacceptable risk zone.
Keywords :
Bayes methods; belief networks; computer network security; data mining; inference mechanisms; pattern classification; risk analysis; Bayesian approach; Bayesian network classifier; DoS attacks; KDD Cup 99 dataset; U2R attacks; association rule mining; classified DoS equally; cyber attackers; cyber situation; cyber situation awareness; cyber threats; denial of service attacks; genetic algorithm; modified risk matrix criteria; network environment; network security; network traffic analysis; risk analysis; user to root attacks; Bayes methods; Intrusion detection; Risk management; Telecommunication traffic; Uncertainty; Bayesian approach; Cyber Situation Awareness; KDD Cup´99; Risk matrix;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on
Conference_Location :
London
Type :
conf
DOI :
10.1109/CyberSA.2015.7166119
Filename :
7166119
Link To Document :
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