Industry 4.0 has risen as an integrated digital manufacturing environment, and it has created a novel research perspective that has thrust research to interdisciplinarity and exploitation of ICT advances. This work presents and discusses the main aspects of Industry 4.0 and how intelligence can be embedded in manufacturing to create the smart factory. It briefly describes the main components of Industry 4.0, and it focuses on the security challenges that the fully interconnected ecosystem of Industry 4.0 has to meet and the threats for each component. Preserving security has a crucial role in Industry 4.0, and it is vital for its existence, so the main research directions on how to ensure the confidentiality and integrity of the information shared among the Industry 4.0 components are presented. Another view is in light of the security issues that come as a result of enabling new technologies.

Business Email Compromise (BEC) attacks have emerged as serious threats to organizations in recent years, exploiting social engineering and malware to dupe victims into divulging confidential information and executing fraudulent transactions. This paper provides a comprehensive review of BEC attacks, including their principles, techniques, and impacts on enterprises. In light of the rising tide of BEC attacks globally and their significant financial impact on business, it is crucial to understand their modus operandi and adopt proactive measures to protect sensitive information and prevent financial losses. This study offers valuable recommendations and insights for organizations seeking to enhance their cybersecurity posture and mitigate the risks associated with BEC attacks. Moreover, we analyze the Greek landscape of cyberattacks, focusing on the existing regulatory framework and the measures taken to prevent and respond to cybercrime in accordance with the NIS Directives of the EU. By examining the Greek landscape, we gain insights into the effectiveness of countermeasures in this region, as well as the challenges and opportunities for improving cybersecurity practices.

Data security plays a crucial role in healthcare monitoring systems, since critical patient information is transacted over the Internet, especially through wireless devices, wireless routes such as optical wireless channels, or optical transport networks related to optical fibers. Many hospitals are acquiring their own metro dark fiber networks for collaborating with other institutes as a way to maximize their capacity to meet patient needs, as sharing scarce and expensive assets, such as scanners, allows them to optimize their efficiency. The primary goal of this article is to develop of an attack detection model suitable for healthcare monitoring systems that uses internet protocol (IP) virtual private networks (VPNs) over optical transport networks. To this end, this article presents the vulnerabilities in healthcare monitoring system networks, which employ VPNs over optical transport layer architecture. Furthermore, a multilayer network architecture for closer integration of the IP and optical layers is proposed, and an application for detecting DoS attacks is introduced. The proposed application is a lightweight implementation that could be applied and installed into various remote healthcare control devices with limited processing and memory resources. Finally, an analytical and focused approach correlated to attack detection is proposed, which can also serve as a tutorial oriented towards even nonprofessionals for practical and learning purposes.

Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Such networks can be very useful in practice, e.g. in the local monitoring of ambient conditions and reporting them to a control center. In this paper we propose a new lightweight, distributed group key establishment protocol suitable for such energy constrained networks. Our approach basically trade-offs complex message exchanges by performing some amount of additional local computations. The extra computations are simple for the devices to implement and are evenly distributed across the participants of the network leading to good energy balance. We evaluate the performance our protocol in comparison to existing group key establishment protocols both in simulated and real environments. The intractability of all protocols is based on the Diffie-Hellman problem and we used its elliptic curve analog in our experiments. Our findings basically indicate the feasibility of implementing our protocol in real sensor network devices and highlight the advantages and disadvantages of each approach given the available technology and the corresponding efficiency (energy, time) criteria

Human activity recognition systems (HARSs) are vital in a wide range of real-life applications and are a vibrant academic research area. Although they are adopted in many fields, such as the environment, agriculture, and healthcare and they are considered assistive technology, they seem to neglect the aspects of security and privacy. This problem occurs due to the pervasive nature of sensor-based HARSs. Sensors are devices with low power and computational capabilities, joining a machine learning application that lies in a dynamic and heterogeneous communication environment, and there is no generalized unified approach to evaluate their security/privacy, but rather only individual solutions. In this work, we studied HARSs in particular and tried to extend existing techniques for these systems considering the security/privacy of all participating components. Initially, in this work, we present the architecture of a real-life medical IoT application and the data flow across the participating entities. Then, we briefly review security and privacy issues and present possible vulnerabilities of each system layer. We introduce an architecture over the communication layer that offers mutual authentication, solving many security and privacy issues, particularly the man-in-the-middle attack (MitM). Relying on the proposed solutions, we manage to prevent unauthorized access to critical information by providing a trustworthy application.