Sage Journals: Discover world-class research

Abstract

Network Security Situation research has become a hot topic in the field of network security, which is expected to solve the network security and management issues. Aiming at the problem of the current security situation of anomaly detection of the time and space complexity is high and not easy to operate, is presented in this paper by collecting a set of network security situation observed samples, detection of network security situation is a feasible method for anomaly by using probability interval, and can predict the variation trend of the current security situation and the abnormal degree, and provide a reliable basis for the network administrator to define decision making and defensive measures, to nip in the bud. Finally, using the simulation data, the abnormal interval estimation and detection algorithm of network security situation is conducted to verify the proposed, results show that the method is correct and has simple and feasible.

Keywords

Network security situation anomaly detection interval estimation probability test

Get full access to this article

View all access options for this article.

References

Bass

, Intrusion detection systems and multisensory data fusion: creating cyberspace situational awareness, Communications of the ACM 43(4) (2000), 99–105.

Zhao

and Liu

, Study on network security situation awareness based on particle swarm optimization algorithm, Computers & Industrial Engineering 125(2) (2018), 764–775.

Bradshaw

J.M.

Carvalho

et al., Sol: an agent-based framework for cyber situation awareness, Künstl Intell Springer 26 (2012), 127–140.

Wen

and Chen

, Network security situation prediction method based on hidden Markov model, Journal of Central South University (Science and Technology) 46(10) (2015), 3689–3695.

Wei

and Fan

, A new method for the prediction of network security situations based on recurrent neural network with gated recurrent unit, International Journal of Intelligent Computing and Cybernetics 11(4) (2018), 511–525.

Erbachera

R.F.

Frinckeb

D.A.

et al., A multi-phase network situational awareness cognitive task analysis, Information Visualization 9(3) (2010), 204–219.

Tang

and Yu

, Method of network security situation prediction based on likelihood BP, Computer Science 36(19) (2009), 97–100, 168.

Zhang

Yang

and Liu

, Quantitative method for network security situation based on attack prediction, Journal on Communications 38(10) (2017), 122–133.

Yang

Qiu

and Wang

, Network security situation evaluation method for multi-step attack, Journal on Communications 38(1) (2017), 187–198.

10.

Guo

and Su

, A new network security situation optimization prediction algorithm based on quantum evolutionary strategy, Mini-Micro Computer System 35(6) (2014), 1248–1252.

11.

Huang

and Zhuang

, A real-time network security situation prediction method, Mini-Micro Computer System 35(2) (2014), 303–306.

12.

Cheng

Jiang

et al., Network anomaly detector based on multiple time series analysis, Advanced Engineering Sciences 49(1) (2017), 144–150.

13.

Han

and Liu

, Research on grey bayesian interval estimation of system parameters in random information, Journal of Southwest China Normal University (Natural Science Edition) 35(5) (2011), 59–61.

14.

Xie

and Ma

, Energy detection algorithm for noise power uncertainty interval estimation and reduced SNR WALL deterioration, Journal of Electronics & Information Technology 36(2) (2014), 364–370.

15.

Zhang

Wang

and Shen

, Interval estimation of sensor fault for linear systems, Control Theory & Applications 35(12) (2018), 1–8.

Research on anomaly detection of network security situation based on interval estimation

Abstract

Keywords

Get full access to this article

References