This is to certify that Prof. Mohit Tiwari has presented a paper on Machine Learning-based Solutions for the Internet of Things (IoT) and Cybersecurity in the 3rd International Conference on Advancement in Electronics & Communication Engineering (Technically Sponsored by IEEE) held on 23rd -24th November, 2023 organized by Department of ECE and Department of CSE at Raj Kumar Goel Institute of Technology, Ghaziabad (U.P.), India

The rapid growth of Internet of Things (IoT) devices has created many security gaps, so we need better defenses. This research looks at using machine learning (ML) to solve cybersecurity problems in IoT networks. By studying network traffic and how devices act, ML models can spot unusual behavior, block threats, and stop unauthorized access in real time. The approach tests several supervised and unsupervised learning methods—such as Support Vector Machines, Random Forests, and Deep Neural Networks—to find the best models for IoT devices that have limited resources. We measure detection accuracy, false‑positive rates, and computational latency to see if the solutions are practical. The study offers clear guidance for building

strong intrusion‑detection systems for diverse IoT networks. Simulations show that predictive modeling can improve data integrity and confidentiality across connected devices. The framework serves as a basic reference for creating adaptive security protocols and provides a systematic way to counter evolving cyber threats in modern communication infrastructures.

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