DETECTING BOTNET ATTACKS IN IOT ENVIRONMENTS: AN OPTIMIZED MACHINE LEARNING APPROACH
DOI:
https://doi.org/10.64751/ajaccm.2025.v5.n4.pp71-77Keywords:
Internet of Things, Botnet Attacks, efficiency, Machine LearningAbstract
The project on "Detecting Botnet Attacks in IoT Environments: An Optimized Machine Learning Approach” addresses the growing threat of botnet attacks in Internet of Things (IoT) ecosystems. The project introduces an advanced machine learning-based solution designed to identify and mitigate botnet activities in IoT devices. The optimized approach focuses on improving accuracy, reducing false positives, and enhancing the overall efficiency of botnet detection in diverse IoT environments.
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31-10-25
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
Mr.A.Anil Kumar Reddy, Yellamsetty Madhuri, Sharla Lokesh, Koray Deekshitha, & Neerudi Krishna Sai. (2025). DETECTING BOTNET ATTACKS IN IOT ENVIRONMENTS: AN OPTIMIZED MACHINE LEARNING APPROACH. American Journal of AI Cyber Computing Management, 5(4), 71-77. https://doi.org/10.64751/ajaccm.2025.v5.n4.pp71-77







