  Industry 5.0, which focuses on human and Artificial Intelligence (AI)
collaboration for performing different tasks in manufacturing, involves a
higher number of robots, Internet of Things (IoTs) devices and
interconnections, Augmented/Virtual Reality (AR), and other smart devices. The
huge involvement of these devices and interconnection in various critical
areas, such as economy, health, education and defense systems, poses several
types of potential security flaws. AI itself has been proven a very effective
and powerful tool in different areas of cybersecurity, such as intrusion
detection, malware detection, and phishing detection, among others. Just as in
many application areas, cybersecurity professionals were reluctant to accept
black-box ML solutions for cybersecurity applications. This reluctance pushed
forward the adoption of eXplainable Artificial Intelligence (XAI) as a tool
that helps explain how decisions are made in ML-based systems. In this survey,
we present a comprehensive study of different XAI-based intrusion detection
systems for industry 5.0, and we also examine the impact of explainability and
interpretability on Cybersecurity practices through the lens of Adversarial
XIDS (Adv-XIDS) approaches. Furthermore, we analyze the possible opportunities
and challenges in XAI cybersecurity systems for industry 5.0 that elicit future
research toward XAI-based solutions to be adopted by high-stakes industry 5.0
applications. We believe this rigorous analysis will establish a foundational
framework for subsequent research endeavors within the specified domain.
