KOU Guang, WANG Shuo, TANG Guangming. Research on Key Technologies of Network Security Situational Awareness for Attack Tracking Prediction[J]. Chinese Journal of Electronics, 2019, 28(1): 162-171. doi: 10.1049/cje.2018.10.007
Citation: KOU Guang, WANG Shuo, TANG Guangming. Research on Key Technologies of Network Security Situational Awareness for Attack Tracking Prediction[J]. Chinese Journal of Electronics, 2019, 28(1): 162-171. doi: 10.1049/cje.2018.10.007

Research on Key Technologies of Network Security Situational Awareness for Attack Tracking Prediction

doi: 10.1049/cje.2018.10.007
Funds:  This work is supported by the National Natural Science Foundation of China (No.61303074) and the Foundation of Science and Technology on Information Assurance Laboratory (No.KJ-15-106).
  • Received Date: 2016-05-03
  • Rev Recd Date: 2018-05-14
  • Publish Date: 2019-01-10
  • This paper analyzed the existing network security situation evaluation methods and discovered that they cannot accurately reflect the features of large-scale, synergetic, multi-stage gradually shown by network attack behaviors. For this purpose, the association between attack intention and network configuration information was deep analyzed. Then a network security situation evaluation method based on attack intention recognition was proposed. Unlike traditional method, the evaluation method was based on intruder. This method firstly made causal analysis of attack event and discovered and simplified intrusion path to recognize every attack phases, then realized situation evaluation based on the attack phases. Lastly attack intention was recognized and next attack phase was forecasted based on achieved attack phases, combined with vulnerability and network connectivity. A simulation experiments for the proposed network security situation evaluation model is performed by network examples. The experimental results show that this method is more accurate on reflecting the truth of attack. And the method does not need training on the historical sequence, so the method is more effective on situation forecasting.
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