# Optimizing Internet of Things Honeypots with Machine Learning: A Review
## 2 Theoretical Background
### Internet of Things  
At its core, the IoT serves as a bridge between the real and virtual worlds, facilitating interactions between physical objects and digital systems. Through the internet, IoT devices collect, process, and share data, enabling real-time monitoring, control, and automation. This connectivity transforms traditional objects into smart devices capable of improving efficiency, optimizing resources, and enhancing user experiences. The concept of IoT has evolved significantly over the decades. The first instance of IoT can be traced back to the mid-1970s at Carnegie Mellon University, where a Coke vending machine was connected to the internet, allowing students to check its status remotely. This early example demonstrated the potential of connected devices long before the term \"IoT\" was coined [15]. In 2005, the International Telecommunication Union (ITU) formally introduced the concept of IoT at the World Summit on the Information Society in Tunisia, presenting it as a revolutionary technology with the potential to reshape global society [15].  
IoT can be simply defined as the integration of sensors, processors, and controllers for actuation, all interconnected via the internet. These systems gather data from the environment, process them, and analyze them to inform decisions or trigger automated actions. Data streams generated by IoT devices can be stored for future reference or processed in real-time to enable immediate responses, making IoT a powerful tool for improving efficiency and enabling autonomous operations. A defining characteristic of IoT is its ability to operate autonomously, minimizing human intervention. IoT systems monitor and control processes independently, ensuring consistent and efficient performance. These systems also optimize resource utilization, reduce delays, and save time, making them invaluable in applications ranging from healthcare to industrial automation. Despite their potential, many IoT devices operate on low-cost hardware, which restricts their ability to perform complex tasks or implement advanced security measures. Additionally, their reliance on low-bandwidth communication channels poses challenges for data-heavy applications and limits the adoption of robust encryption, increasing their vulnerability to attacks. The deployment of IoT devices in physically insecure or hostile environments further exposes them to risks. Remote management and the absence of manual control make it difficult to monitor and secure these devices effectively. Many IoT systems also rely on Radio Frequency Identification (RFID) technology, which is vulnerable to eavesdropping, spoofing, and other security threats, adding to the challenges of ensuring safe operations [16]. IoT systems are susceptible to a variety of security threats, including sinkhole, HELLO flood, wormhole, and Sybil attacks. In a sinkhole attack, a malicious node disrupts communication by attracting and manipulating traffic within the network. HELLO flood attacks involve flooding the network with false messages, leading to instability and data loss. Wormhole attacks tunnel data between distant nodes, creating routing disruptions, while Sybil attacks see a malicious node assuming multiple identities, enabling network manipulation or denial of service. These threats underscore the importance of robust security measures in IoT environments [16].  
The IoT represents a groundbreaking shift in how the physical and digital worlds interact. By connecting real-world objects to the internet, IoT enables intelligent systems that enhance efficiency and autonomy. However, the challenges of resource limitations and security vulnerabilities must be addressed to fully realize its potential. As IoT continues to evolve, it remains a cornerstone of innovation across industries, offering unprecedented opportunities for connectivity and automation.