A Comprehensive Analysis of Various Threat Detection and Prevention Techniques in IoT Environment

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The Internet of Things (IoT) has become one of the most widely used technologies in recent times. IoT devices can be enabled to collect, and exchange information in a highly efficient manner via the network. A smart object with technology and devices builds a network infrastructure that is used in a variety of areas such as mechanical, building, medical, manufacturing, entertainment, and transport. The major security issues such as confidentiality, authentication, confirmation, security systems, system configuration, data storage, and administration are the main challenges in an IoT environment. To overcome these security issues, various techniques are addressed. Initially software called an Intrusion Detection System (IDS) was used that monitors a network of malicious activity using valuable tools in IoT devices. Then, the machine technique was used to detect the attacks from the intrusion detection system to provide embedded intelligence in IoT devices and networks. Finally, Blockchain (BC) technology is gaining traction in modern IoT devices to address security and privacy challenges to provide reliable communication in an IoT environment. The aim of this work is to provide a detailed review of ML and BC techniques that can be used to develop revamped IoT security devices.