Retrieval of Information Through Botnet Attacks

Author:

Ismail Zahian1ORCID,Jantan Aman B.2,Yusoff Mohd. Najwadi2,Kiru Muhammad Ubale2

Affiliation:

1. Universiti Malaysia Pahang, Malaysia

2. Universiti Sains Malaysia, Malaysia

Abstract

Services and applications online involve information transmitted across the network, and therefore, the issue of security during data transmission has become crucial. Botnet is one of the prominent methods used by cybercriminals to retrieve information from internet users because of the massive impact cause by the bot armies. Thus, this chapter provides a study of Botnet and the impact of Botnet attacks especially on the security of information. In order to survive, Botnet implemented various evasion techniques, and one of the notorious ones is by manipulating an encrypted channel to perform their C&C communication. Therefore, the authors also review the state of the art for Botnet detection and focus on machine learning-based Botnet detection systems and look into the capabilities of machine learning approaches to detect this particular Botnet. Eventually, they also outline the limitations of the existing Botnet detection approach and propose an autonomous Botnet detection system.

Publisher

IGI Global

Reference53 articles.

1. A proposal of metrics for botnet detection based on its cooperative behavior.;M.Akiyama;2007 International Symposium on Applications and the Internet Workshops,2007

2. Al-Azzawi. (2014). Detection of P2P Botnets Based on SVN. Journal of Engineering & Technology, 32(A).

3. Al-Hammadi, Y. A. A. (2010). Behavioural correlation for malicious bot detection. Doctor. Retrieved March 22, 2019, from http://etheses.nottingham.ac.uk/1359/

4. Angrishi, K. (2017). Turning Internet of Things(IoT) into Internet of Vulnerabilities (IoV) : IoT Botnets. Retrieved April 22, 2019, from http://arxiv.org/abs/1702.03681

5. Binkley, J. R., & Singh, S. (2006). An Algorithm for Anomaly-based Botnet Detection. Proceedings of the 2nd Conference on Steps to Reducing Unwanted Traffic on the Internet SRUTI’06, 7. Retrieved from http://dl.acm.org/citation.cfm?id=1251303

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