Cybersecurity challenges in energy harvesting systems: A machine learning approach to safeguarding industrial IoT networks Book in Scopus uri icon

abstract

  • This chapter delves into the critical issue of industrial cybersecurity attacks in the context of energy harvesting (EH) technologies. As EH gains momentum in various industrial applications, the integration of smart devices and the Internet of Things (IoT) introduces new cybersecurity challenges. This study comprehensively examines the emerging threats and vulnerabilities associated with EH systems in industrial environments. This chapter analyzes a spectrum of cyberattack vectors that can compromise the integrity, availability, and confidentiality of data and control systems within EH networks. These attack vectors include malware injection, Denial-of-Service (DoS) attacks, firmware manipulation, and supply chain vulnerabilities. Moreover, the research explores the potential consequences of successful cyberattacks on EH infrastructure, ranging from production disruptions to equipment damage and financial losses. Understanding these risks is essential for industries to develop robust cybersecurity strategies. To mitigate these threats, the chapter identifies current best practices and effective mitigation measures for safeguarding EH systems. In addition, real-world case studies of cyberattacks on EH systems in industrial settings provide valuable insights into attacker tactics and techniques. The chapter emphasizes the significance of collaboration and information sharing among industry stakeholders, government agencies, and cybersecurity experts to fortify the overall security posture of EH infrastructure. The chapter also highlights the pressing need for proactive and comprehensive cybersecurity measures in industrial EH. It focuses on potential threats and the adoption of effective countermeasures in order to ensure the secure and sustainable growth of energy harvesting technologies while safeguarding critical infrastructures from cyberattacks.

publication date

  • January 1, 2026