Enterprise Information Systems
AI-enabled security and privacy for Fog Computing and Industrial Internet of Things
About the issue:
We have entered an era of information technology booming and integration, whereby many different technologies have their own impacts and can integrate with other technologies with other impacts. There are no exceptions to AI and security. With the rapid development in each of AI and security, the integration can make it more consolidated against different types of attacks, which have become more sophisticated, aggressive and organized. Therefore, AI-based and AI-security security will be essential for development in the 21st century.
The rapid advancement in Fog Computing and the Industrial Internet of Things (IIoT) can make security and privacy more challenging due to various reasons. To sum everything up in brief, they are as follows. First, it opens up more ports and possibilities for unauthorized access in Fog Computing and IIoT. Second, more users and data have been on Fig Computing and IIoT, and some hackers see the opportunities for hacking. Third, new features and functions in systems have not been fully tested or fully integrated, which require some workaround, and users or system managers may not be fully aware of security vulnerabilities. Last, as previously discussed, the techniques to gain unauthorized access have improved. Therefore, sophisticated techniques will be required. This allows AI-based/AI-enabled security and privacy to take challenges forward.
The AI-enabled security and privacy approaches provide a better alternative as follows. First, the defense can be in real-time and live. Any abnormal activities can be reported to the systems, system managers and key users live to provide better security warnings. Second, since integration can be challenging and there are more functions, data and users to manage, AI-based approaches can provide protection and monitoring for all of them. Third, the AI-enabled approaches provide more consolidated security and privacy features to defend different types of attacks simultaneously. Therefore, in this special issue, we look for the latest development, innovation and solutions for all types of AI-enabled security and privacy for Fog Computing and IIoT. We consider all types of recommendations and solutions if authors can demonstrate novelty, hybrid integration between AI and security, new methods, theoretical and applied research contributions, well-written English and so on. Additionally, top authors from FEMIB 2021 and IIoTBDSC 2021 and related events will be invited.
The goal of this special issue is to collect high-quality theoretical and applied contributions in topics including, but are not limited to:
Innovative techniques integrating AI and security platforms and services for Fog Computing and/or IIoT
Large scale simulations, penetration testing and ethical hacking for Fog Computing and/or IIoT
Innovative and intelligent algorithms to enhance security, privacy, performance, mentoring and intrusion detection and prevention.
Innovative and modern encryption signature and forensics for AI-enabled Fog Computing and/or IIoT
Privacy-preserving analytic and predictive models for integrated AI-enabled Fog Computing and/or IIoT.
Modern blockchain techniques for secure AI-enabled Fog Computing and/or IIoT.
AI-enabled 5G and 6G for Fog Computing and/or IIoT.
AI-enabled security and privacy
AI-enabled security and privacy for Fog Computing and IIoT
Any successful prototypes and real-world solutions demonstrating both theoretical and applied contributions
Deadline for submissions: 03 January 2022
Notification of First Round: 31 March 2022
Final Decision: 31 August 2022
Original papers describing completed and unpublished work not currently under review by any other journal/magazine/conference/workshop are solicited. Previously published conference/ symposia/ workshop papers or technical reports MUST be clearly clarified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue. Prospective authors should submit via the submission site of Enterprise Information Systems. Submitting authors must answer ‘Yes’ to a question of “Is this submission for a special issue?” and then select “Security and Privacy for IoT and Big Data” from the drop-down menu.
Victor Chang (Lead Guest Editor)
Teesside University, UK
Singapore Management University, Singapore