Submit a Manuscript to the Journal
Information Security Journal: A Global Perspective
For a Special Issue on
Machine Intelligence and data analytics for Cybersecurity in the industry 4.0 era
Manuscript deadline
15 January 2024

Special Issue Editor(s)
Yassine Maleh,
Sultan Moulay Slimane University, Morocco
[email protected]
Loai A Tawalbeh,
Texas A&M Universityn San Antonio, USA
[email protected]
Imed Romdhani,
Edinburgh Napier University, UK
[email protected]
Karim Ouazzane,
London Metropolitan University
[email protected]
Machine Intelligence and data analytics for Cybersecurity in the industry 4.0 era
Digital transformation, also known as Industry 4.0, Smart Industry and Smart Manufacturing, is at the top of leaders' agendas. Such a transformation stimulates innovation in new products and services, the digital transformation of processes and the creation of new business models and ecosystems. In the world of manufacturing, Industry 4.0 is based on various technological advances, among which we can mainly cite CPS (cyber-physical systems), IoT (internet of things), and IoS (internet of services).
While interesting, this fourth wave also brings with it significant challenges for manufacturers. Business operations and the supply chain are becoming more vulnerable to cyber threats.
During the COVID-19 pandemic, cybersecurity was the focus of particular attention. In response to the crisis, many manufacturers adopted teleworking to ensure their employees' health and safety as well as business continuity. However, this change has made them more vulnerable to cyber attackers, who actively seek to take advantage of these uncertain times.
Machine Intelligence and data analytics techniques have shown potential in providing various methods for threat detection.
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This special issue aims to explore research on new machine Intelligence and data analytics techniques for cybersecurity in the industry 4.0 era. Possible topics include, but are not limited to:
- Big Data Analytics for Cybersecurity in industry 4.0
- Artificial Intelligence Analytics Techniques for cyber-physical systems
- Machine Learning techniques for Cybersecurity and Privacy in smart systems
- Deep Learning techniques for Cybersecurity in smart grid
- Malware detection and prevention techniques for industry 4.0 applications
- Intrusion and cybersecurity threat detection and analysis
- Cyber-physical-social system security and incident management
- IoT cybersecurity and privacy
- Big data analytics for Cybersecurity in smart city
- Cybercrime and digital forensics in IoT and cloud computing;
- AI for Cybersecurity in SCADA systems;
- Cybersecurity and privacy in industrial control systems;