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Overview

With the incremental integration of technologies, the Next Generation Cyber-Physical Systems (NG-CPS) have evolved into complex, autonomous, sophisticated, and ubiquitous. Thus, today's NG-CPS, which includes the Internet of Things, Cyber components, Internet of Vehicles, intelligent implantable medical devices (IMDs), etc., has caught the interest of both academics and industry. Although NG-CPS can be distinguished by a set of prospects for both service providers (industry and market stakeholders) and pros-consumers (clients). Despite the fact that NG-CPS technology has several advantages, but, at the same time, it offers a number of challenges such as reliability, security, and interoperability for involved stakeholders. Among these challenges, security is one of the most worrisome concerns that hamper the future deployment of this technology.

To tackle the security-related challenges associated with the NG-CPS technology, the literature suggested various schemes, but somehow, they are unable to detect newly adopted security threats. Therefore, it is a must-need situation to design reliable Artificial intelligence (AI)-driven security counteractions schemes for NG-CPS technology to address these concerns cost-effectively. To explore, AI-driven solutions should be used as an alternative technology in the presence of existing literature because it has the capability to predict and detect previously and newly adopted attacks from the network traffic behavior. With the transformation of AI-driven techniques in NG-CPS, the security of these networks can be improved up to a great extent. Therefore, we believe that the researchers and industry experts need to work collectively to design new AI-driven solutions for this emerging technology.

The purpose of this Special Issue is to bring together leading researchers from academia and industry to discuss their visions, recent findings, and future insights related to AI-driven cybersecurity solutions for the NG-CPS technology.
Potential topics include, but not limited to the following :

All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in the submission menu http://hcisj.com/submission/preparing_manuscript.php
All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select “SI2022-08AI-driven Cybersecurity”. when they reach the “Article Type” step in the submission process https://mc04.manuscriptcentral.com/hcis.