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Network Security Evaluation Based on Support Vector Machine

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 225))

Abstract

Network safety risk assessment of the solution is a key part of network security. Support vector machine method to overcome the defects of the traditional evaluation method (such as neural network method) of the nonlinear and local minimum value. This paper describes the content and index of network safety risk assessment, and puts forward a network safety risk assessment method based on support vector machine. The experimental results show that the method is feasible and effective.

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References

  1. Feng DG, Zhang Y, Zhang YQ (2010) Survey of information security risk evaluation. J China Inst Commun 1(7):24–28

    Google Scholar 

  2. Wang R, Jie C (2011) Enhancing training set for face detection based on SVM. J Softw 2(5):74–78

    Google Scholar 

  3. Wang XD, Shi Z, Wu C (2011) An improved algorithm for dectsion-tree-based SVM. In: Proceeding of the 6th world congress on intelligent control and automation, vol 3(4), pp 4235–4239

    Google Scholar 

  4. Li G, Cheng C, Lin J (2007) Short-term load forecasting using support vector machine with SCE-UA algorithm. In: Third international conference on natural computation (ICNC), vol 4(5), pp 112–115

    Google Scholar 

  5. Bernhard School Kopf, Sung K-K et al (2009) Comparing support vector machines with Gaussian kernels to radical basis function classifiers. IEEE Trans Signal Process 5(11):2758–2765

    Google Scholar 

  6. Li X, Liu J, Shi Z (2009) A Chinese web page classifier based on support vector machine and unsupervised clustering. Chin J Comput 6(3):1174–1178

    Google Scholar 

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Correspondence to Xiang Chen .

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© 2013 Springer-Verlag Berlin Heidelberg

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Chen, X., Li, Y. (2013). Network Security Evaluation Based on Support Vector Machine. In: Yang, Y., Ma, M. (eds) Proceedings of the 2nd International Conference on Green Communications and Networks 2012 (GCN 2012): Volume 3. Lecture Notes in Electrical Engineering, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35470-0_6

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  • DOI: https://doi.org/10.1007/978-3-642-35470-0_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35469-4

  • Online ISBN: 978-3-642-35470-0

  • eBook Packages: EngineeringEngineering (R0)

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