NDLI: A framework for network security situation awareness based on knowledge discovery

Content Provider	IEEE Xplore Digital Library
Author	Fang Lan Wang Chunlei Ma Guoqing
Copyright Year	2010
Description	Author affiliation: Department of Network Research, Institute of System Engineering, Beijing, China (Fang Lan; Ma Guoqing) \|\| Department of Computer Science, Tsinghua University, Beijing, China (Wang Chunlei)
Abstract	Network security situation awareness provides the unique high level security view based upon the security alert events. But the complexities and diversities of security alert data on modern networks make such analysis extremely difficult. In this paper, we analyze the existing problems of network security situation awareness system and propose a framework for network security situation awareness based on knowledge discovery. The framework consists of the modeling of network security situation and the generation of network security situation. The purpose of modeling is to construct the formal model of network security situation measurement based upon the D-S evidence theory, and support the general process of fusing and analyzing security alert events collected from security situation sensors. The generation of network security situation is to extract the frequent patterns and sequential patterns from the dataset of network security situation based upon knowledge discovery method and transform these patterns to the correlation rules of network security situation, and finally to automatically generate the network security situation graph. Application of the integrated Network Security Situation Awareness system (Net-SSA) shows that the proposed framework supports for the accurate modeling and effective generation of network security situation.
File Size	559566
File Format	PDF
ISBN	9781424463473
e-ISBN	9781424463497
DOI	10.1109/ICCET.2010.5486194
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Data security network security data mining Data engineering Large scale integration knowledge discovery Data mining situation awareness Computer science Information security Intrusion detection Systems engineering and theory Computer security
Content Type	Text
Resource Type	Article

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