Abstract
Alert Correlation is a key part of intrusion detection technique. Traditional methods based on the situation awareness techniques usually store the different dimensions of security information in separate knowledge bases, which leads to the lack of synergies between the various dimensions. For complex attacks, it is difficult to integrate all context information quickly to launch real-time and accurate analysis. To address these issues, we proposed an integrated intelligent security event correlation analysis system, named KGBIAC, which uses knowledge graph to represent and store the network security information. We explain the structure of KGBIAC and conduct an experiment on the DARPA 2000 dataset. Performance evaluation shows that the KGBIAC performs potentially effective.
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Acknowledgements
This work is supported by the National Key Research and Development Program No. 2016YFB0800804, No. 2016YFB0800803, No. 2016YFB0800802
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Wang, W., Jiang, R., Jia, Y., Li, A., Chen, Y. (2017). KGBIAC: Knowledge Graph Based Intelligent Alert Correlation Framework. In: Wen, S., Wu, W., Castiglione, A. (eds) Cyberspace Safety and Security. CSS 2017. Lecture Notes in Computer Science(), vol 10581. Springer, Cham. https://doi.org/10.1007/978-3-319-69471-9_41
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DOI: https://doi.org/10.1007/978-3-319-69471-9_41
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