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Erschienen in:
2014 | OriginalPaper | Buchkapitel
7. Incorporating Uncertainty in Intrusion Detection to Enhance Decision Making
verfasst von : Lane Harrison, Aidong Lu
Erschienen in: Scientific Visualization
Verlag: Springer London
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Abstract
Network security defense often involves uncertain data which can lead to uncertain judgments regarding the existence and extent of attacks. However, analytic uncertainty and false positive decisions can be integrated into analysis tools to facilitate the process of decision making. This paper presents an interactive method to specify and visualize uncertain decisions to assist in the detection process of network intrusions. Uncertain decisions on the degree of suspicious activity for both temporal durations and individual nodes are integrated into the analysis process to aide in revealing hidden attack patterns. Our approach has been implemented in an existing security visualization system, which is used as the baseline for comparing the effects of newly added uncertainty visualization component. The case studies and comparison results demonstrate that uncertainty visualization can significantly improve the decision making process for attack detection.