Explainable Embodied and Agentic AI for Cybersecurity and Digital Forensics

The increasing complexity of digital ecosystems and the rapid evolution of cyber threats demand intelligent, transparent, and adaptive security solutions. Traditional cybersecurity and digital forensic approaches are increasingly insufficient to address sophisticated, large-scale, and dynamic attacks. Emerging paradigms such as Explainable Artificial Intelligence (XAI), Agentic AI, and Embodied AI provide transformative opportunities to enhance cybersecurity resilience and digital forensic capabilities.Agentic AI introduces autonomous, goal-driven systems capable of proactive threat detection, adaptive decision-making, and automated response. Explainable AI ensures transparency, interpretability, and accountability in AI-driven security operations, which is critical for trust, regulatory compliance, and forensic validation. Embodied AI extends intelligence into cyber-physical environments, including Internet of Things (IoT) devices, drones, and smart systems, where cyber incidents can have physical and societal consequences.Despite these advances, key challenges remain, including lack of standardized explainability frameworks, vulnerability to adversarial attacks, limited real-world deployment of autonomous agents, and issues surrounding the forensic admissibility of AI-generated evidence. This Research Topic aims to bring together interdisciplinary contributions that explore novel frameworks, models, and applications leveraging Explainable, Agentic, and Embodied AI to strengthen cybersecurity and digital forensic practices. Contributions addressing real-world applications, evaluation frameworks, and cross-domain integration are particularly encouraged.This Research Topic aims to address the need for intelligent, transparent, and autonomous systems in cybersecurity and digital forensics. It focuses on leveraging Explainable AI, Agentic AI, and Embodied AI to enhance threat detection, incident response, and forensic analysis.Key knowledge gaps include the absence of robust explainability mechanisms in high-stakes security systems, limited integration of agent-based AI in operational cybersecurity environments, and insufficient methodologies for ensuring the reliability and legal admissibility of AI-driven forensic evidence. Emerging research questions include how to balance autonomy with human oversight, how to design robust AI systems resistant to adversarial manipulation, and how embodied AI systems can operate securely in distributed and resource-constrained environments.The goal is to develop scalable, trustworthy, and explainable AI-driven solutions that improve decision-making, strengthen cyber defense mechanisms, and support reliable digital forensic investigations.Cybersecurity and digital forensics are undergoing a paradigm shift with the integration of artificial intelligence. Traditional reactive and rule-based approaches are no longer sufficient to counter evolving cyber threats. AI-driven systems offer enhanced capabilities for threat detection, anomaly identification, and automated response.Explainable AI addresses the critical need for transparency in decision-making processes, particularly in high-stakes environments where accountability and auditability are essential. Agentic AI enables autonomous and adaptive systems capable of proactive defense. Embodied AI extends these capabilities to cyber-physical systems such as IoT devices, drones, and smart infrastructures.However, challenges such as trust, robustness, interoperability, and legal compliance remain significant barriers. Addressing these challenges is essential for the adoption of AI-driven solutions in real-world cybersecurity and digital forensic applications.This Research Topic welcomes submissions on theoretical, methodological, and applied aspects of Explainable AI, Agentic AI, and Embodied AI in cybersecurity and digital forensics. Topics of interest include:• Explainable AI for cybersecurity analytics and forensic investigations • Autonomous and agent-based AI for threat detection and response • Embodied AI for securing IoT, UAVs, and cyber-physical systems • Adversarial machine learning and robust AI system design • AI-driven digital forensic frameworks and evidence validation • Human-AI collaboration and trust in security operations • Privacy, ethics, and regulatory challenges in AI-enabled security • Real-world deployments and case studies We welcome Original Research, Review, Methods, Data, and Perspective articles. Submissions demonstrating practical impact, interdisciplinary approaches, and real-world applicability are strongly encouraged. Topic editors: Áine MacDermott, Farkhund Iqbal Source: https://www.frontiersin.org/research-topics/80447/explainable-embodied-and-agentic-ai-for-cybersecurity-and-digital-forensics