# A Holistic Review of Machine Learning Adversarial Attacks in IoT Networks
## 2 Background
### Internet of Things Overview  
The IoT is one of the cutting-edge technologies in Industry 4.0, where the term \"Things\" refers to smart devices or objects interconnected through wireless networks [44; 45]. These \"Things\" range from everyday household objects to advanced industrial instruments capable of sensing, gathering, transmitting, and analyzing data. Such capabilities facilitate smart decision-making and services enhancing both human life quality and industrial production.  
At present, there is no agreed-upon structure for IoT architecture. The fundamental framework of IoT comprises three layers: the perception layer, the network layer, and the application layer [46]. Yet, based on the requirements for data processing and making  
Figure 3: Key security and privacy features of IoT network.  
intelligent decisions, a support or middleware layer, positioned between the network and application layers, was later deemed to be essential [47]. Different technologies are utilized within each of these layers, introducing various challenges and security concerns [2; 48]. Figure 4 shows the four-layered IoT architecture showing various devices, technologies, and applications along with possible security threats at each layer. * Perception layer: The bottom layer of any IoT framework involves \"things\" or endpoint objects that serve as the bridge between the physical and the digital worlds. The perception or sensing layer refers to the physical layer, encompassing sensors and actuators capable of gathering information from the real environment and transmitting it through wireless or wired connections. This layer can be vulnerable to security threats such as insertion of fake data, node capturing, malicious code, side-channel attacks, jamming attacks, sniffing or snooping, replay attacks, and sleep deprivation attacks. * Network layer: It is known as the second layer connecting the perception layer and middleware layer. It is also called the communication layer because it acts as a communication bridge, enabling the transfer of data acquired in the perception layer to other interconnected devices or a processing unit, conversely. This transmission utilizes various network technologies like LTE, 5G, Wi-Fi, infrared, etc. The data transfer is executed securely, ensuring the confidentiality of the obtained information. Nonetheless, persistent security vulnerabilities can manifest as data transit attacks, phishing, identity authentication, and encryption attacks, and distributed denial-of-service (DDoS/DoS) attacks. * Middleware layer: It is also commonly known as the support layer or processing layer. It is the brain of the IoT ecosystem, and its primary functions are data processing, storage, and intelligent decision-making. The middleware layer is the best candidate to implement advanced IoT security mechanisms, such as ML-based security systems, thanks to its high computation capacity. Therefore, it is also a target of adversarial attacks and other various attacks such as SQL injection attacks, cloud malware injection, insider attacks, signature wrapping attacks, man-in-the-middle attacks, and cloud flooding attacks. * Application layer: It is the uppermost layer within the IoT architecture. It serves as the user interface to monitor IoT devices and observe data through various application services and tools, such as dashboards and mobile applications, as well as applying various control activities by the end user. There are various use cases for IoT applications such as smart homes and cities, smart logistics and transportation, and smart agriculture and manufacturing. This layer is also subject to various security threats  
Figure 4: Four-layered IoT architecture and corresponding security issues.  
such as sniffing attacks, service interruption attacks, malicious code attacks, reprogramming attacks, access control attacks, data breaches, application vulnerabilities, and software bugs.