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Mathematical Problems in Engineering
Volume 2017, Article ID 4934082, 9 pages
https://doi.org/10.1155/2017/4934082
Research Article

An Effective Conversation-Based Botnet Detection Method

1School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
2Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China

Correspondence should be addressed to Xiaosong Zhang; nc.ude.ctseu@sxznosnhoj

Received 25 January 2017; Accepted 12 March 2017; Published 9 April 2017

Academic Editor: Lixiang Li

Copyright © 2017 Ruidong Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [8 citations]

The following is the list of published articles that have cited the current article.

  • Meisam Eslahi, Wardah Zainal Abidin, and Maryam Var Naseri, “Correlation-based HTTP Botnet detection using network communication histogram analysis,” 2017 IEEE Conference on Application, Information and Network Security (AINS), pp. 7–12, . View at Publisher · View at Google Scholar
  • Zhimin Guo, Zhuo Lv, Boyang Zhou, and Cen Chen, “Feature detection and security evaluation of mobile phone based on decision tree,” 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp. 89–92, . View at Publisher · View at Google Scholar
  • Abdurrahman Pektaş, and Tankut Acarman, “Botnet detection based on network flow summary and deep learning,” International Journal of Network Management, vol. 28, no. 6, 2018. View at Publisher · View at Google Scholar
  • Chun-Yu Wang, Chi-Lung Ou, Pin-Hao Chen, Jyh-Biau Chang, Yu-En Zhang, Feng-Min Cho, and Ce-Kuen Shieh, “BotCluster: A session-based P2P botnet clustering system on NetFlow,” Computer Networks, vol. 145, pp. 175–189, 2018. View at Publisher · View at Google Scholar
  • Mayank Raheja, Prachi Ahlawat, and Lakshya Mathur, “Botnet Detection via mining of network traffic flow,” Procedia Computer Science, vol. 132, pp. 1668–1677, 2018. View at Publisher · View at Google Scholar
  • Noemí DeCastro-García, Ángel Luis Muñoz Castañeda, Mario Fernández Rodríguez, and Miguel V. Carriegos, “On Detecting and Removing Superficial Redundancy in Vector Databases,” Mathematical Problems in Engineering, vol. 2018, pp. 1–14, 2018. View at Publisher · View at Google Scholar
  • Abdurrahman Pektaş, and Tankut Acarman, “Deep learning to detect botnet via network flow summaries,” Neural Computing and Applications, 2018. View at Publisher · View at Google Scholar
  • Sergii Lysenko, Kira Bobrovnikova, Oleg Savenko, and Andrii Kryshchuk, “BotGRABBER: SVM-Based Self-Adaptive System for the Network Resilience Against the Botnets’ Cyberattacks,” Computer Networks, vol. 1039, pp. 127–143, 2019. View at Publisher · View at Google Scholar