Abstract
The rapid development of information technology exposes peoples life and work to the network. While people are enjoying in sharing their resources in the convenient condition, network security issues have emerged. Instead of considering security of single device in the network, researchers have shown an increased interest to grasp the overall network situation as a big picture in order to create situation awareness which consists of event detection, situation assessment and situation prediction. As the highest level in situation awareness, Network Security Situation Prediction makes quantitative prediction of incoming network security posture based on historical and present security situation information. The purpose is to provide an informational reference to network managers for helping them in formulating and implementing timely preventive measures before the network is under attack. In this paper, the authors group the existing network security situation prediction mechanisms into three major categories and review each model in the aspect of its strengths and limitations. The authors conclude that adaptive Grey Verhulst is more suitable to be used in predicting incoming network security situation.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
2014 Data Breach Investigations Report. pp. 1-60. United States: Verizon Enterprise (2014)
Xynos, K., Sutherland, L., Blyth, A.: Effectiveness of Blocking Evasions in Intrusion Prevention System. University of South Wales, pp. 1–6 (2013)
Endsley, M.R.: Situation Awareness Global Assessment Technique (SAGAT). In: 1988 National Aerospace and Electronics Conference, pp. 789–795. IEEE Press (1998)
Bass, T.: Intrusion Detection Systems and Multisensor Data Fusion. Communications of the ACM 43(4), 99–105 (2000)
McCulloch, W.S., Pitts, W.: A Logical Calculus of the Ideas Immanent in Nervous Activity. The Bulletin of Mathematical Biophysics 5(4), 115–133 (1943)
Li, J., Dong, C.: Research on Network Security Situation Prediction-Oriented Adaptive Learning Neuron. In: Second International Conference on Networks Security Wireless Communications and Trusted Computing (NSWCTC), pp. 483–485. IEEE Press (2010)
Wei, X., Jiang, X.: Comprehensive Analysis of Network Security Situational Awareness Methods and Models. In: 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA), pp. 176–179. IEEE Press (2013)
Xi, R., Jin, S., Yun, X., Zhang, Y.: CNSSA: A Comprehensive Network Security Situation Awareness System. In: IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 482–487. IEEE Press (2011)
Lin, Z., Chen, G., Guo, W., Liu, Y.H.: PSO-BPNN-based Prediction of Network Security Situation. In: 3rd International Conference on Innovative Computing Information and Control, pp. 37–41. IEEE Press (2008)
Zhang, Y., Jin, S., Cui, X., Yin, X., Pang, Y.: Network Security Situation Prediction Based on BP and RBF Neural Network. In: Yuan, Y., Wu, X., Lu, Y. (eds.) ISCTCS 2012. CCIS, vol. 320, pp. 659–665. Springer, Heidelberg (2013)
Tang, C., Xie, Y., Qiang, B., Wang, X., Zhang, R.: Security Situation Prediction Based on Dynamic BP Neural with Covariance. Procedia Engineering 15, 3313–3317 (2011)
Tang, C., Wang, X., Zhang, R., Xie, Y.: Modeling and Analysis of Network Security Situation Prediction Based on Covariance Likelihood Neural. In: Huang, D.-S., Gan, Y., Premaratne, P., Han, K. (eds.) ICIC 2011. LNCS, vol. 6840, pp. 71–78. Springer, Heidelberg (2012)
Zheng, R., Zhang, D., Wu, Q., Zhang, M., Yang, C.: A Strategy of Network Security Situation Autonomic Awareness. In: Lei, J., Wang, F.L., Li, M., Luo, Y. (eds.) NCIS 2012. CCIS, vol. 345, pp. 632–639. Springer, Heidelberg (2012)
Lai, J.B., Wang, H.Q., Liu, X.W., Liang, Y., Zheng, R.J., Zhao, G.S.: WNN-based Network Security Situation Quantitative Prediction Method and Its Optimization. Journal of Computer Science and Technology 23(2), 222–230 (2008)
Zhang, Q., Benveniste, A.: Wavelet Networks. IEEE Transactions on Neural Networks 3(6), 889–898 (1992)
Chen, F., Shen, Y., Zhang, G., Liu, X.: The Network Security Situation Predicting Technology Based on the Small-world Echo State Network. In: 4th IEEE International Conference on Software Engineering and Service Science, pp. 377–380. IEEE Press (2013)
Jaeger, H.: Tutorial on Training Recurrent Neural Networks, Covering BPPT, RTRL, EKF and the” Echo State Network” Approach. GMD-Forschungszentrum Informationstechnik (2002)
Cortes, C., Vapnik, V.: Support-vector Networks. Machine Learning 20(3), 273–297 (1995)
Cheng, X., Lang, S.: Research on Network Security Situation Assessment and Prediction. In: Fourth International Conference on Computational and Information Sciences, pp. 864–867. IEEE Press (2012)
GuangCai, K., XiaoFeng, W., LiRu, Y.: A Fuzzy Forecast Method for Network Security Situation Based on Markov. In: International Conference on Computer Science and Information Processing, pp. 785–789 (2012)
Man, D., Wang, Y., Wu, Y., Wang, W.: A Combined Prediction Method for Network Security Situation. In: International Conference on Computational Intelligence and Software Engineering, pp. 1–4. IEEE Press (2010)
Wang, Y., Li, W., Liu, Y.: A Forecast Method for Network Security Situation Based on Fuzzy Markov Chain. In: Huang, Y.-M., Chao, H.-C., Deng, D.-J. (eds.) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. LNEE, vol. 260, pp. 953–962. Springer, Heidelberg (2014)
Ju Long, D.: Control Problems of Grey Systems. Systems & Control Letters 1(5), 288–294 (1982)
Deng, J.-L.: Introduction to Grey System Theory. The Journal of Grey System 1(1), 1–24 (1989)
Deng, J.-L.: Modelling of the GM model of Grey Systems, pp. 40–53 (1988)
Deng, J.-L.: Properties of the Grey Forecasting Model of GM(1,1). Grey System, pp. 79–90 (1988)
Liu, S., Forrest, J., Yang, Y.: A Brief Introduction to Grey Systems Theory. Grey Systems: Theory and Application 2(2), 89–104 (2012)
Kordnoori, S., Mostafaei, H., Kordnoori, S.: The Application of Fourier Residual Grey Verhulst and Grey Markov Model in Analyzing the Global ICT Development. Hyperion Economic Journal 2(1), 50–60 (2014)
Hu, W., Li, J.-H., Chen, X.-Z., Jiang, X.-H.: Network Security Situation Prediction Based on Improved Adaptive Grey Verhulst Model. Journal of Shanghai Jiaotong University (Science) 15, 408–413 (2010)
Jibao, L., Huiqiang, W., Liang, Z.: Study of Network Security Situation Awareness Model Based on Simple Additive Weight and Grey Theory. In: International Conference on Computational Intelligence and Security, pp. 1545–1548. IEEE Press (2006)
Zhang, F., Wang, J., Qin, Z.: Using Gray Model for the Evaluation Index and Forecast of Network Security Situation. In: International Conference on Communications, Circuits and Systems, pp. 309–313. IEEE Press (2009)
Juan, L., Tao, L., Gang, L.: A Network Security Dynamic Situation Forecasting Method. In: International Forum on Information Technology and Applications, pp. 115–118. IEEE Press (2009)
Diangang, W., Xuemei, H., Sunjun, L., Kui, Z.: Research on Network Security Situation Awareness Technology Based on Artificial Immunity System. In: International Forum on Information Technology and Applications, pp. 472–475. IEEE Press (2009)
Rongzhen, F., Mingkuai, Z.: Network Security Awareness and Tracking Method by GT. Journal of Computational Information Systems 9(3), 1043–1050 (2013)
Liu, S.F., Lin, Y.: An Introduction to Grey Systems Theory. IIGSS Academic Publisher, Grove City (1998)
Guo, Z., Song, X., Ye, J.: A Verhulst Model on Time Series Error Corrected for Port Throughput Forecasting. Journal of the Eastern Asia society for Transportation studies 6, 881–891 (2005)
Wang, Z., Dang, Y., Wang, Y.: A New Grey Verhulst Model and Its Application. In: International Conference on Grey Systems and Intelligent Services, pp. 571–574. IEEE Press (2007)
Wen, K.-L., Huang, Y.-F.: The Development of Grey Verhulst Toolbox and the Analysis of Population Saturation State in Taiwan-Fukien. In: International Conference on Systems, Man and Cybernetics, pp. 5007–5012. IEEE Press (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Leau, YB., Manickam, S. (2015). Network Security Situation Prediction: A Review and Discussion. In: Intan, R., Chi, CH., Palit, H., Santoso, L. (eds) Intelligence in the Era of Big Data. ICSIIT 2015. Communications in Computer and Information Science, vol 516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46742-8_39
Download citation
DOI: https://doi.org/10.1007/978-3-662-46742-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46741-1
Online ISBN: 978-3-662-46742-8
eBook Packages: Computer ScienceComputer Science (R0)