Analysing the Role of Supervised and Unsupervised Machine Learning in IoT
Kushal Rashmikant Dalal
20202020 International Conference on Electronics and Sustainable Communication Systems (ICESC)44 citationsDOI
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.
Topics & Concepts
Unsupervised learningComputer scienceArtificial intelligenceReinforcement learningMachine learningSupervised learningSemi-supervised learningInternet of ThingsArtificial neural networkComputer securityMachine Learning and ELMNetwork Security and Intrusion DetectionInternet of Things and AI