Abstract
In recent years, with the development of computer technology and communication technology, computer networks have developed rapidly to become an indispensable part of people's lives. In the same time, network attacks have been increasing exponentially. Countries around the world have raised network security issues to the height of their national strategies, which shows the importance of network security. Firewall is an important technology for network security at present, and it is a barrier to protect the internal network. However, in the era of information explosion, the data flow of network communication is very large, due to the limitations of memory, CPU, etc., firewalls will become a communication bottleneck. Therefore, this paper introduces the idea of machine learning into the filtering rules of the decision tree, and uses the optimized decision tree C4.5 algorithm to predict the optimal ranking of the firewall filtering rule table attributes, which improves the efficiency of the firewall and thus the throughputs of the firewall.
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References
Xiren, X.: Computer Network. Electronic Industry Press, Beijing (2009)
Noonan, W., Dubrawsky, I.: Firewall Foundation. People’s Posts and Telecommunications Press, Beijing (2007)
Xiangbin, H., Cong, Z.: Research on dynamic optimization of firewall rules based on Huffman tree. Comput. Moderniz. 8, 207–215 (2010)
Li, Z.: Research on Firewall Optimization Based on Statistical Analysis Method. Chongqing University, Chongqing (2011)
Anxi, R., Shoubao, Y., Hongwei, L.: A firewall rule matching optimization method based on statistical analysis. Comput. Eng. Appl. 42(4), 162–164 (2006)
Qingwei, Z., Aiying, F.: Firewall Technical Standard Course. Beijing Institute of Technology Press, Beijing (2010)
Malik, S.: CCIE#4955.2 Principles and Practice of Network Security. Beijing: People's Posts and Telecommunications Press (2008)
Qun, W.: Extraordinary Network Management-Network Foundation. People's Posts and Telecommunications Press, Beijing (2006)
Jiawei, H.: Data Mining: Concept and Technology. Mechanical Industry Press, Beijing (2012)
Jing, Y., Nannan, Z., Jian, L., Yanming, L., Meihong, L.: Research and application of decision tree algorithm. Comput. Technol. Dev. 20(02), 114–116+120 (2010)
Shaorong, F.: Research and improvement of decision tree algorithm. J. Xiamen Univ. (Nat. Sci. Ed.) 04, 496–500 (2007)
Sun Lin, X., Jiucheng, M.Y.: Decision tree rule extraction method based on new conditional entropy. Comput. Appl. 04, 884–887 (2007)
Jingqiong, Z.: Research on Firewall Technology Based on Learning. Nanjing University of Science and Technology, Nanjing (2004)
Weiping, W., Wenhui, C., Zupeng, L., Huaping, C.: Firewall policy inconsistency detection algorithm. J. Graduate Univ. Chin. Acad. Sci. 24(3), 378 (2007)
Jiaye, W., Jiwu, J., Sencun, Z. Security research of packet filtering firewall. Comput. Sci. 1999(08): 34–36+42 (1999)
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Jin, Y., Wang, Q. (2021). Firewall Filtering Technology and Application Based on Decision Tree. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_17
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DOI: https://doi.org/10.1007/978-3-030-78612-0_17
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