Impact of the Industrial Internet of Things (IIoT) on Cybersecurity within Industry 4.0: A Systematic Review of Literature - Sánchez Rosas, Luis Junior; Vega Solis, Edwin Rolando; Paico Egusquiza, Ayle Jarumy; Mendoza Vasquez, Ari Anielka (LACCEI, 2025)
The accelerated growth of the Industrial Internet of Things (IIoT) has driven the need for advanced and secure anomaly detection solutions, especially in industrial environments where cybersecurity is critical. This study provides a Systematic Literature Review (SLR) guided by the PRISMA 2020 method, with the objective of identifying the impact of IIoT on cybersecurity within Industry 4.0. Thirty-two studies published between 2020 and 2024 in academic databases such as Scopus and Web of Science were reviewed. The results reveal that emerging technologies such as Blockchain, Machine Learning and Deep Learning are playing a central role in data protection and intrusion detection in IIoT systems. Blockchain has proven to be effective in ensuring data integrity and improving operational efficiency. This review highlights the importance of adopting robust cybersecurity solutions to mitigate risks and strengthen resilience in Industry 4.0 and suggests key areas for future research in this field.