Application of Machine Learning for IoT Security: A Step Toward Society 5.0
Swapnil Morandé, Veena Tewari, Mohit Kukreti, Aarti Dangwal, Tahseen Arshi, Amitabh Mishra · 2023
The research demonstrates the application of machine learning (ML) while keeping the information security aspect of IoT devices in mind. It explains the significance of the Internet of Things (IoT) and expands on associated challenges, in line with the goal of transitioning to “Society 5.0.” It shows how machine learning can be used to maintain IoT security using a quantitative approach. The research design includes machine learning-based data analysis of 95 samples collected from IoT devices, as well as anomaly detection methods to identify compromised data. The study goes on to explain how to use machine learning for the security of IoT devices, highlighting anomaly detection as an essential technique in the process. Because the use of IoT in sensitive areas necessitates careful consideration, the research suggests deploying machine learning as a security measure. Finally, it reflects on how successful anomaly detection in machine learning can assist organizations in detecting and responding to information security risks in real time.