MATEC Web Conf.
Volume 228, 20182018 3rd International Conference on Circuits and Systems (CAS 2018)
|Number of page(s)||5|
|Section||Intelligent Computing and Information Processing|
|Published online||14 November 2018|
An Attack Threat Effect Analysis Method Based on K-Means Evaluation
State Grid Fujian Electric Power Research Institute, 350000 Fuzhou, China
2 State Grid Henan Electric Power Company, 450000 Zhengzhou, China
3 Global Energy Interconnection Research Institute CO., LTD. 210000 Nanjing, China
To take full advantage of the specified features of the attack dataset in network attack effect evaluation, maximize the efficiency of evaluation without losing its accuracy. This paper proposed a K-Means evaluation technique using dimensional entropy components, derived from changes in network entropy through attack period and the advantages of clustering algorithm in data mining. This method makes a pre-process of the attack dataset on the basis of network entropy, mapping it to a two-dimensional plane and utilize the output of pre-process as the input of clustering. Then establish a relation between the attack dataset and the effect category via an improved K-Means algorithm, thus achieving an explicit division of attack effect set and provide efficient evaluation result. The experimental results prove that the method can process attack dataset with high efficiency, as well as provide a visualized evaluation result by the form of cluster tree.
Key words: Marketing Safe / Effect evaluation / K-Means algorithm
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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