| Title | Analysing the Role of Supervised and Unsupervised Machine Learning in IoT |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Dalal, Kushal Rashmikant |
| Conference Name | 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC) |
| Keywords | Classification algorithms, Clustering algorithms, Internet of Things (IoT), machine learning, Malware, ML techniques, security, supervised learning, Supervised Learning and Unsupervised Learning, Support vector machines, unsupervised learning |
| Abstract | 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. |
| DOI | 10.1109/ICESC48915.2020.9155761 |
| Citation Key | dalal_analysing_2020 |
Analysing the Role of Supervised and Unsupervised Machine Learning in IoT