**1. Introduction**

Internet of Things is a widespread, intelligent network composed of smart devices that enables the implementation of advanced services in housing, manufacturing, transport, health, and other sectors, as well as enabling a new ecosystem for application development. Examples of widespread IoT systems include the following:


IoT devices share the sensor data they collect by connecting to an IoT gateway or other edge device—from where the data is sent to the cloud to be stored and analyzed. The data can also be analyzed locally on edge devices—in real time.

Today, with more connected "things" than the population of the Earth, the issue of IoT security is a major challenge [1]. More billions of IoT devices increases the threat and opens up the possibility of numerous attacks on the devices themselves. To address these security challenges, it is essential to explore frameworks like the 'Security Framework for Internet of Things proposed by El-Gendy and Azer [2]. Hacked devices cause disruption of connectivity and can also serve as a starting point for attacks on other devices and systems. The issue of confidentiality, availability, and integrity of data is greater than ever; therefore, it is necessary to ensure the functionality of CIA (Confidentiality, Integrity, Availability) through encryption and other protection methods.

Many authors have researched the appearing attacks and risks of the IoT devices:


Many IoT vulnerabilities could be mitigated with recognized security best practices, but too many products today do not include even basic security measures. There are many factors that contribute to this lack of security. It is unclear who is responsible for security decisions in a situation where one company designs the device, another supplies the component software, a third manages the network in which the device is embedded, and a fourth uses the device. This challenge is compounded by the lack of comprehensive, widely adopted international regulations—norms and standards for IoT security. Addressing the growing concerns about IoT security, it is vital to consider existing security protocols as highlighted in Maamar et al.'s comprehensive survey of Internet of Things security protocols [6]. Moreover, exploring recent surveys, such as the work by Alaba et al. [7], can provide valuable insights into the overall landscape of Internet of Things security.

Given the numerous incidents in the past few years that exploited IoT devices and ecosystems, countries have begun to recognize and be aware of the problem. In order for the IoT to function in a secure environment in the future, they started to formally standardize and legally regulate the Internet of Things and adhere to the best security practices.

*Methods for Detection and Prevention of Vulnerabilities in the IoT (Internet of Things) Systems DOI: http://dx.doi.org/10.5772/intechopen.113898*

However, advancements in robotics, such as the integration of anthropometric robots, offer potential solutions to enhance IoT security. For example, the use of mobile anthropometric robots with their ability to interact with the IoT infrastructure can improve security measures by enabling monitoring, threat detection, and response capabilities in IoT environments [8].

In addition to security protocols and surveys, it is essential to recognize the role of intrusion detection systems (IDS) in safeguarding IoT environments. Gupta et al. conducted a survey focused on intrusion detection systems in wireless sensor networks [9], shedding light on their significance in enhancing security in IoT ecosystems.

In our research, we have implemented and tested an intrusion detection system (IDS) at an egg/poultry farm Vezeshari. Our IDS was based on Snort—open-source signature-based intrusion detection system. We have set up the system rules to detect four types of IoT attacks: dynamic login attempts, XML injection attacks, SQL injection attacks, and Firmware (command) injection attacks. All of these attacks utilized code injections that target the wireless layer of the IoT system. The wireless frames from different Wi-Fi components of the IoT system are prone to these attacks, so we tested injection attacks at these points. To test our IDS, we invited ethical hackers from multiple countries that conducted orchestrated attack attempts. In most of the cases (over 80%), our IDS was able to detect and alert on the attack attempts—and the results are presented in Section 5. Our IDS is signature-based and to overcome its limitations, we plan to follow Tacker's et al. approach [10] that implements an anomaly-based IDS based on machine learning, and it will be our future research.

This chapter is organized as follows: in Section 2, we elaborate on the vulnerability risks of IoT systems; in Section 3, we present risk prevention and management for the IoT systems; in Section 4, we explain the usage of intrusion detection and prevention systems (IDS/IPS). In Section 5, a real-world use case (Vezeshari's IDS) is presented with methodology and key results, and then in Section 6, we give final conclusions.
