Author:
Mardini-Bovea Johan,Salcedo Dixon,Nagles-Pozo Issac,Quiñonez Yadira,Mejía Jezreel
Publisher
Springer Nature Switzerland
Reference47 articles.
1. Kabir, E., Hu, J., Wang, H., & Zhuo, G. (2018). A novel statistical technique for intrusion detection systems. Future Generation Computer Systems, 79, 303–318.
2. Khraisat, A., Gondal, I., Vamplew, P. (2018). An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier. In: Ganji, M., Rashidi, L., Fung, B., Wang, C. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2018. Lecture Notes in Computer Science(), vol 11154. Springer, Cham.
3. Zhu, G., Yuan, H., Zhuang, Y., Guo, Y., Zhang, X., & Qiu, S. (2021). Research on network intrusion detection method of power system based on random forest algorithm. In IEEE 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), Beihai, China, 2021, pp. 374–379.
4. Garfinkel, S., & Spafford, G. (1997). Web security & commerce (pp. 349–374). O’reilly.
5. Lehtinen, R., & Gangemi Sr, G. T. (2006). Computer security basics: computer security. “ O'Reilly Media, Inc.“.