An efficient botnet detection approach based on feature learning and classification

Abstract

Bot detection is considered a crucial security issue that is extensively analysed in various existing approaches. Machine Learning is an efficient way of botnet attack detection. Bot detection is the major issue faced by the existing system. This research concentrates on adopting a graph-based feature learning process to reduce feature dimensionality. The incoming samples are correctly classified and optimised using an Adaboost classifier with an improved grey wolf optimiser (g-AGWO). The proposed IGWO optimisation approach is adopted to fulfil the multi-constraint issues related to bot detection and provide better local and global solutions (to satisfy exploration and exploitation). The extensive results show that the proposed g-AGWO model outperforms existing approaches to reduce feature dimensionality, under-fitting/over-fitting and execution time. The error rate prediction shows the feasibility of the given model to work over the challenging environment. This model also works efficiently towards the unseen data to achieve better generalization.

KEYWORDS:

• Botnet
• machine learning
• AdaBoost
• grey wolf optimisation
• exploration
• exploitation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

B. Padmavathi

B. Padmavathi was born in Tiruchirappalli, Tamil Nadu, India, on 19th November 1982. She received her ME degree from the Department of Computer Science and Engineering, Anna University, Tiruchirappalli, India. She is pursuing her PhD degree in School of Computing from Sathyabama Institute of Science and Technology, Chennai, India. She is currently working as an assistant professor in Easwari Engineering College, Chennai, India. She has 16 years of experience in teaching. Her current research interest includes Network Security, Machine Learning and Big Data Analytics.

B. Muthukumar

B. Muthukumar was born in Nagercoil, Tamil Nadu, India, on 25th July 1975. He received an MCA degree from the Manonmaniam Sundaranar University, Thirunelveli, Tamil Nadu, India, in 1999 and ME degree from Sathyabama University, Chennai, Tamil Nadu, India, in 2004. He obtained his PhD degree from Sathyabama University, Chennai, Tamil Nadu, India, in 2013. He has 17 years of experience in teaching. He is currently working as a professor in DMI College of Engineering, Chennai, Tamil Nadu, India, and his area of interest include Cloud Computing, Machine Learning and Networks Cryptography.