Abstract
The Internet of Things (IoT) is a technological innovation that has revolutionized society. The IoT will forever change the way we use simple things that do very little things to smart, fully capable things. IoT devices can process and automate everyday household and workplace tasks through simple sensors. Yet despite the benefits of these devices, they are vulnerable to violations such as privacy issues and security breaches. This paper aims to provide a clearer understanding of the IoT and current threats to it by explaining why IoT devices are susceptible to attack. Moreover, the technologies used in the IoT are examined, as well as the different communication layers of the IoT and their functioning. The findings reveal that IoT devices are prone to many software and hardware vulnerabilities, not to mention the challenges that come with IoT. Solutions to these challenges are proposed, notably through the use of anomaly-based intrusion detection systems, which are critical components of network security. Using machine learning (ML) to detect potential attacks is recommended. Many proposed anomaly-based detection systems use different ML algorithms and techniques. However, there is no standard benchmark to compare these in terms of power consumption. A benchmark that measures both accuracy and power consumption to calculate and evaluate each algorithm's implementation is proposed.