Analysing the Role of Supervised and Unsupervised Machine Learning in IoT

Analysing the Role of Supervised and Unsupervised Machine Learning in IoT

연구 분야: Artificial Intelligence

학회: 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC)

To harness the value of data generated from IoT, there is a crucial requirement of new mechanisms. Machine learning (ML) is among the most suitable paradigms of computation which embeds strong intelligence within IoT devices. Various ML techniques are being widely utilised for improving network security in IoT. These techniques include reinforcement learning, semi-supervised learning, supervised learning, and unsupervised learning. This report aims to critically analyse the role played by supervised and unsupervised ML for the enhancement of IoT security.