Internet of Things (IoT) devices are not only finding increasing use in ordinary households, but they have also become a key element for the Industry 4.0 concept. The implementation of industrial IoT devices into production streamlines the production process and reduces production costs. On the other hand, connected IoT devices bring new security risks to production and expose an industrial environment to new types of attacks. The article analyzes the vulnerability of the production line with implemented industrial IoT devices with consideration of a possible Distributed Denial-of-service (DDoS) attack led by attackers from the internet. Various types of DDoS attacks abusing the presence of IoT devices in the system were performed on an automated production line implementing sorting, preparation, and dosing of bulk and liquid materials for filling into containers. The leading attacks caused failure of the production line during the production, as well as the dysfunction of communication with IoT devices. The article also demonstrates the implementation of countermeasures against DDoS attacks and possible strategies to protect and mitigate such attacks on the production line.

Smart devices along with sensors are gaining in popularity with the promise of making life easier for the owner. As the number of sensors in an Internet of Things (IoT) system grows, a question arises as to whether the transmission between the sensors and the IoT devices is reliable and whether the user receives alerts correctly and in a timely manner. Increased deployment of IoT devices with sensors increases possible safety risks. It is IoT devices that are often misused to create Distributed Denial of Service (DDoS) attacks, which is due to the weak security of IoT devices against misuse. The article looks at the issue from the opposite point of view, when the target of a DDoS attack are IoT devices in a smart home environment. The article examines how IoT devices and the entire smart home will behave if they become victims of a DDoS attack aimed at the smart home from the outside. The question of security was asked in terms of whether a legitimate user can continue to control and receive information from IoT sensors, which is available during normal operation of the smart home. The case study was done both from the point of view of the attack on the central units managing the IoT sensors directly, as well as on the smart-home personal assistant systems, with which the user can control the IoT sensors. The article presents experimental results for individual attacks performed in the case study and demonstrates the resistance of real IoT sensors against DDoS attack. The main novelty of the article is that the implementation of a personal assistant into the smart home environment increases the resistance of the user’s communication with the sensors. This study is a pilot testing the selected sensor sample to show behavior of smart home under DDoS attack.

Modern manufacturing systems are influenced by the growing complexity of mechatronics, control systems, IIoT, and communication technologies integrated into cyber-physical systems. These systems demand flexibility, modularity, and rapid project execution, making digital tools critical for their design. Virtual commissioning, based on digital twins, enables the testing and validation of control systems and designs in virtual environments, reducing risks and accelerating time-to-market. This research explores the development of digital twin models to bridge the gap between simulation and real-world validation. The models identify design flaws, validate the PLC control code, and ensure interoperability across software platforms. A case study involving a modular Festo manufacturing system modelled in Tecnomatix Process Simulate demonstrates the ability of digital twins to detect inefficiencies, such as collision risks, and to validate automation systems virtually. This study highlights the advantages of virtual commissioning for optimizing manufacturing systems. Communication testing showed compatibility across platforms but revealed limitations with certain data types due to software constraints. This research provides practical insights into creating robust digital twin models, improving the flexibility, efficiency, and quality of manufacturing system design. It also offers recommendations to address current challenges in interoperability and system performance.

Industry 4.0 collects, exchanges, and analyzes data during the production process to increase production efficiency. Internet of Things (IoT) devices are among the basic technologies used for this purpose. However, the integration of IoT technology into the industrial environment faces new security challenges that need to be addressed. This is also true for a production line. The production line is a basic element of industrial production and integrating IoT equipment allows one to streamline the production process and thus reduce costs. On the other hand, IoT integration opens the way for network cyberattacks. One possible cyberattack is the increasingly widely used distributed denial-of-service attack. This article presents a case study that demonstrates the devastating effects of a DDOS attack on a real IoT-based production line and the entire production process. The emphasis was mainly on the integration of IoT devices, which could potentially be misused to run DDoS. Next, the verification of the proposed solution is described, which proves that it is possible to use the sampled flow (sFlow) stream to detect and protect against DDoS attacks on the running production line during the production process.

Optimizing the energy efficiency of robotic workstations is a key aspect of industrial automation. This study focuses on the analysis of the relationship between the position of the robot base and its energy consumption and time aspects. A number of 6-axis robots, including the ABB IRB 120 robot, were investigated in this research by combining measurements and simulations using the energy consumption measurement module in the ABB RobotStudio 2024.1.1 environment. The objective of this study was to develop an energy consumption model that can identify the optimal robot positions to minimize energy costs and time losses. The results suggest that the strategic positioning of the robot has a significant impact on its performance and efficiency. These results demonstrate that the ideal working distance of the robots is approximately 50% of its maximum range, and displacements along the X and Z axes affect the energy and time consumption. These findings suggest the existence of a trade-off between time and energy efficiency, providing a basis for further research into the optimization of robotic systems. Thus, this work offers new perspectives for the design of efficient robotic workstations for cross-sensory applications.

IoT devices and their fast growth on the Internet cause many cyber-attacks problems. The number of compromised IoT devices can be used by DDoS (Distributed Denial of Service) attackers to imitate valid request packet or to form illegal request packet to the victim with a spoofed source IP addresses to hide themselves, meanwhile giving rise the system collapse, the obstruction of network/traffic, or disrupting of the victim Internet operation. In this article is demonstrated a specific kind of DDoS attack involving usually accessible IoT devices - the UDP-based Distributed Reflective DoS Attack (DRDoS). The packets are flooded by the attacker to the IoT device as a reflector with a source IP address set to the IP address of the victim who obtains the reflected replies and can be overloaded. To examine this kind of attack, there has to be four representatives of heterogeneous IoT devices involved: an IP camera, a smart light-bulb, a network printer, and a small single-board computer Raspberry Pi. This article illustrates the possibility of the IoT devices to be integrated into DRDoS attack and to flood a network as well as their potential to form a targeted attack on a narticular victim machine.