Current Trends in Data Security and Privacy—2nd Edition

Dear Colleagues,

Industry 4.0 encompasses a broad range of advanced technologies that collectively enable highly integrated, intelligent, and autonomous digital manufacturing environments. The resulting hyper-connected industrial ecosystem introduces a complex and evolving threat landscape, as each interconnected component, platform, and service becomes a potential attack vector. Ensuring robust security is therefore a fundamental prerequisite for the viability and sustainability of Industry 4.0 systems. In this context, a central challenge lies in guaranteeing the confidentiality, integrity, and availability of data exchanged across heterogeneous industrial assets, cyber–physical systems, and organizational boundaries.

The rapid proliferation of the Internet of Things (IoT), together with the increasing convergence of information technology (IT) and operational technology (OT) infrastructures, further amplifies the need for enhanced cyber resilience and effective privacy protection. The expansive attack surface created by large numbers of interconnected devices, combined with the complexity of IoT-driven industrial processes, enables increasingly sophisticated cyber–physical attack scenarios. As a result, Industry 4.0 infrastructures and IoT-based applications can only realize their full potential if security and privacy challenges are addressed in a systematic, scalable, and resilient manner.

At the same time, the growing integration of artificial intelligence (AI) and machine learning technologies within Industry 4.0 environments introduces both novel threats and powerful defensive capabilities. AI-driven techniques can be abused to automate, scale, and adapt cyberattacks, facilitating advanced intrusion, evasion, and manipulation strategies targeting industrial systems. Conversely, AI is increasingly employed to strengthen security and privacy controls through intelligent monitoring, anomaly and threat detection, predictive risk assessment, and adaptive response mechanisms. Balancing the secure and trustworthy deployment of AI with the mitigation of AI-enabled threats—particularly with respect to robustness, explainability, data protection, and governance—constitutes a critical research challenge in next-generation industrial ecosystems.

This Special Issue aims to attract high-quality research contributions that address fundamental challenges, emerging threats, and state-of-the-art solutions related to data security and privacy in Industry 4.0 technologies and applications.

Prof. Dr. Chrysostomos Stylios
Dr. Vasiliki Liagkou
Dr. Kyriakos Stefanidis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Cybersecurity and Privacy is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• cybersecurity and privacy in industrial environments
• security in cyber–physical environments
• cryptography and post-quantum cryptography in I4.0
• security and privacy in industrial control systems
• system and network security
• privacy protection and privacy-by-design
• trust issues in intelligent IoT devices
• threat detection and risk management
• incident response and vulnerability management
• secure data management and trading
• privacy-enhancing technologies
• artificial intelligence (AI)-based security
• standardization activities for I4.0 security