Federated AI Models for Distributed Network Botnet Detection
Keywords:
Federated Learning, Botnet Detection, Distributed Networks, Privacy-Preserving AIAbstract
Distributed network security is threatened by botnets' complexity and massive attacks. Botnet detection centralized solutions may have privacy and scalability difficulties. Federated AI methods detect large botnets in this research. Federated learning trains machine learning models across network nodes so local data is protected. It discusses federated learning, distributed systems, and botnet detection. Data heterogeneity, communication cost, and model convergence plague federated AI botnet detection. Federated AI identifies botnets in real life. We conclude with future research and how federated AI may improve scattered network cybersecurity.
Downloads
References
Madupati, Bhanuprakash. "AI's Impact on Traditional Software Development." arXiv preprint arXiv:2502.18476 (2025).
Pillai, Vinayak. Anomaly Detection for Innovators: Transforming Data into Breakthroughs. Libertatem Media Private Limited, 2022.
Madupati, Bhanuprakash. "The Role of AI in the Public Sector: A Technical Perspective." Available at SSRN 5076600 (2024).
Konda, Bhargavi, et al. "Enhancing Traceability and Security in mHealth Systems: A Proximal Policy Optimization-Based Multi-Authority Attribute-Based Encryption Approach." 2025 29th International Conference on Information Technology (IT). IEEE, 2025.
Gondaliya, Jayraj, et al. "Hybrid security RSA algorithm in application of web service." 2018 1st International Conference on Data Intelligence and Security (ICDIS). IEEE, 2018.
Madupati, Bhanuprakash. "AI-Driven Threat Detection in Cybersecurity." Available at SSRN 5076610 (2024).
Yadulla, Akhila Reddy, Bhargavi Konda, and Vinay Kumar Kasula. "Blockchain for Secure Communication." Blockchain Applications for the Energy and Utilities Industry. IGI Global Scientific Publishing, 2025. 103-140.
Kalluri, Kartheek. "Revolutionizing Computational Material Science with ChatGPT: A Framework for AI-Driven Discoveries."
Madupati, Bhanuprakash. "The Role of Cybersecurity in Combating Digital Crime-A Technical Perspective." Available at SSRN 5076618 (2024).
Pawar, Priyanka, et al. "Exploring Blockchain-Enabled Secure Storage and Trusted Data Sharing Mechanisms in IoT Systems." 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). Vol. 3. IEEE, 2025.
Nair, Sreejith Sreekandan, et al. "Safeguarding Tomorrow-Fortifying Child Safety in Digital Landscape." 2024 International Conference on Computing, Sciences and Communications (ICCSC). IEEE, 2024.
Kalluri, Kartheek, and Abhilash Kokala. "Performance Benchmarking Of Generative Ai Models: Chatgpt-4 Vs. Google Gemini Ai."
Madupati, Bhanuprakash, Anil Kumar Jonnalagadda, and Supriya Madupathi. "A Technical Comparison of ChatGPT and DeepSeek: Architecture, Efficiency, and Performance." International Journal of Global Innovations and Solutions (IJGIS) (2025).
Kumar, K. Kishore, et al. "Electro Cardio Gram Using Different Machine Learning Techniques for Early Heart Attack Prediction." Journal of Neonatal Surgery 14.19s (2025): 769-776.
Kalluri, Kartheek. "Revolutionizing Bpm: The Role of Low-Code/No-Code Platforms in Accelerating Business Process Automation."
Madupati, Bhanuprakash, and Supriya Madupathi. "Building Scalable and Efficient Graphql Apis: Strategies, Optimization, and Best Practices." International Journal of Global Innovations and Solutions (IJGIS) (2025).
Shankeshi, Raghu Murthy. "The Role of AI in Enhancing Data Security and Compliance in Oracle Cloud Infrastructures." American Journal of Data Science and Artificial Intelligence Innovations 3 (2023): 53-67.
Kalluri, Kartheek, et al. "Transforming Education: Exploring the Potential of VR and AR in Online Learning Systems." Available at SSRN 5204089 (2025).
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
