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As an extension of cloud services to the edge, Fog computing is a current paradigm for latency-sensitive and resource-constrained applications. Nevertheless, its distributed architecture makes it vulnerable to sophisticated cybersecurity threats, especially botnet assaults. To tackle this problem, we propose a reinforcement learning–enhanced deep learning framework for multi-class classification of botnet attacks in a fog computing environment. At the heart of our approach is a Bidirectional Long Short-Term Memory (BiLSTM) network, a well-known sequential data modeling network. Reinforcement learning based feature selection was used to find and retain the best relevant set of attributes such that detection can be maximized. We performed extensive experimentation and evaluated over four cross-validation folds using a real-life dataset. This proposed model consistently proved micro-averaged precision, recall, F-score, and accuracy greater than 95% on all classes — namely High, Moderate, Low, and Normal attack intensities — over three benchmarked datasets, BADD, RLUF, and DIBCA. Particularly, precision and sensitivity scores were relatively close to perfect, ranging from near-perfect scores for higher severity attacks in terms of detection and false alarms. By proving that deep learning can be further improved by incorporating reinforced feature optimization, this study provides evidence that deep learning can be further boosted to assist in fog networks with deep botnet detection. The proposed framework is ready to adapt, efficient, and holds great promise for real-time intrusion detection based on Internet of Things (IoT) backed fog infrastructures.
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India
Surya Pavan Kumar Gudla is currently a Research Scholar at BPUT, Rourkela, and holds MCA and M.Tech degrees from Jawaharlal Nehru Technological University, Kakinada (JNTUK). With 14 years of teaching experience in engineering education, Mr. Gudla has consistently demonstrated a strong commitment to academia. He is presently serving at the Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, INDIA – 532201. Mr. Gudla’s research contributions are well recognized, with multiple publications in esteemed international journals and conferences. His work on attack detection frameworks and deep learning models for IoT systems has received notable attention, particularly through contributions to IEEE conferences and Springer volumes. Demonstrating a forward-thinking approach, he has co-authored two patents and two text book titled Artificial Intelligence and Soft Computing – Fundamentals and Cloud Computing reflecting his commitment to advancing technological frontiers. To date, he has published 15 papers in reputed national and international journals and conferences, underscoring his dedication to academic excellence and innovation in his field.""""""
India
PREETI NUTIPALLI is currently serving as an Assistant Professor in the Department of Computer Science and Engineering at ANITS, Sangivalasa, India. She earned her M.Tech. degree in Computer Science and Engineering from JNTU Kakinada in 2013 and brings over 15 years of teaching experience to her academic role. Her primary research interests include cloud computing, cybersecurity, and optimization techniques. She has published several scholarly articles in reputed international journals and conferences, authored one academic book, and holds two patents in her field of expertise. Mrs. Nutipalli is the recipient of the Young Women Researcher Award in recognition of her contributions to research and innovation. She remains deeply passionate about teaching, academic excellence, and fostering research-driven education in engineering.
India
Dr. Yegireddi Ramesh has been working as Professor & HOD in the Department of CSE at Aditya Institute of Technology and Management (A), Tekkali, Srikakulam permanently affiliated with Jawaharlal Nehru Technological University Vizianagaram, Andhra Pradesh, India. He completed his Bachelor of Science (B.Sc) from Andhra University. He completed a Master of Computer Applications (MCA) from Osmania University, Master of Technology (M.Tech - CSE) from JNTUH Hyderabad and Ph D (CSE) from JNTUK Kakinada. He filed one International Patent, was published WIPO PCT, and also filed 3 Indian Patents (including 1 - Design), among them one granted and other are published in Indian Patent Journal, Govt. of India. He secured one Copyright which was granted by the Copyright Office, Government of India. He also wrote three Textbooks entitled A Methodical Observation of the Analysis of Cryptographic Algorithms, Integrating AI, Big Data, and Cyber Security for next generation Communication and Networking Systems, and Internet of Things. . He published 30 Research papers in various reputed (UGC approved, Scopus/ SCI / Web of Science) International and National Journals, magazines, and conferences. He is also a reviewer for International Journal of Research and Development in Engineering Sciences (IJRDES-2582- 4201)). He has more than 24 years of experience in teaching and research and also has good knowledge of Information Security, Networks, Data Science, Blockchain and Internet of Things along with academic subjects, etc. He guided 35 UG and 20 PG academic projects. Currently, he is an active member of ISTE, CSI, and ACM.
India
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: Surya Pavan Kumar Gudla, pavan1980.mca@gmail.com Preeti Nutipalli, preethinutipalli7@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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