Safety, Security and Privacy in Machine Learning Based Internet of Things

[EN] Recent developments in communication and information technologies, especially in the internet of things (IoT), have greatly changed and improved the human lifestyle. Due to the easy access to, and increasing demand for, smart devices, the IoT system faces new cyber-physical security and privacy...

ver descrição completa

Detalhes bibliográficos
Autores: Abbas, Ghulam, Mehmood, Amjad, Carsten, Maple, Epiphaniou, Gregory, Lloret, Jaime|||0000-0002-0862-0533
Tipo de documento: artigo
Data de publicação:2022
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositório:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglês
OAI Identifier:oai:riunet.upv.es:10251/202173
Acesso em linha:https://riunet.upv.es/handle/10251/202173
Access Level:Acceso aberto
Palavra-chave:Internet of things (IoT)
Machine learning
Security and privacy
CPS
INGENIERÍA TELEMÁTICA
Descrição
Resumo:[EN] Recent developments in communication and information technologies, especially in the internet of things (IoT), have greatly changed and improved the human lifestyle. Due to the easy access to, and increasing demand for, smart devices, the IoT system faces new cyber-physical security and privacy attacks, such as denial of service, spoofing, phishing, obfuscations, jamming, eavesdropping, intrusions, and other unforeseen cyber threats to IoT systems. The traditional tools and techniques are not very efficient to prevent and protect against the new cyber-physical security challenges. Robust, dynamic, and up-to-date security measures are required to secure IoT systems. The machine learning (ML) technique is considered the most advanced and promising method, and opened up many research directions to address new security challenges in the cyber-physical systems (CPS). This research survey presents the architecture of IoT systems, investigates different attacks on IoT systems, and reviews the latest research directions to solve the safety and security of IoT systems based on machine learning techniques. Moreover, it discusses the potential future research challenges when employing security methods in IoT systems.