Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices
Jeyabharathi, A. Sherly Alphonse, E.L. Dhivya Priya, M. Kowsigan · 2021
The Internet of Things (IoT) connects various devices into a network for providing smart and intelligent services. But this paves the way for hackers and security breaches. There are different security solutions based on machine learning techniques. This chapter presents the machine learning techniques commonly used for intrusion detection, malware detection, and anomaly detection. Intrusion is a common security breach in the IoT Services as they use Wireless Sensor Networks. The chapter identifies the different types of attacks and the IoT authentication processes. Botnet attacks in IoT applications are a major threat to security. Botnet attacks pave the way for other attacks like Distributed Denial of Service attacks (DDoS), spying of organization and identity theft. Constrained by botnet administrators by means of Command-and-Control-Servers (C&C Server), they are frequently utilized by criminals for activities such as taking private data, misusing web-based financial information, DDos-assaults or for spam and phishing messages.