The Internet of Things consists of an interconnected network of devices used in a multitude of different environments. The objective of this paper is to give a comprehensive look at the state of the art of IoT system defense mechanisms, analysing case studies and offering thoughts on which models are the most promising, particularly focusing on machine learning and deep learning techniques.
L’Internet of Things consiste in una rete interconnessa di dispositivi usati in una moltitudine di ambienti diversi. L’obiettivo dell’elaborato è quello di dare una prospettiva completa dello state dell’arte dei meccanismi di difesa dei sistemi IoT, analizzando casi di studio e offrendo riflessioni su quali sono i modelli più promettenti, in particolare concentrandosi sulle tecniche di machine learning e deep learning.
ANALISI DI TECNICHE E APPROCCI BASATI SUL MACHINE LEARNING PER LA SICUREZZA DEI SISTEMI INTERNET OF THINGS
SURIANO, FRANCESCO
2021/2022
Abstract
The Internet of Things consists of an interconnected network of devices used in a multitude of different environments. The objective of this paper is to give a comprehensive look at the state of the art of IoT system defense mechanisms, analysing case studies and offering thoughts on which models are the most promising, particularly focusing on machine learning and deep learning techniques.I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.14253/88469