Artificial Intelligence (AI) has become a cornerstone of modern Security Operations Centers (SOCs), enabling intelligent threat detection, malware analysis, anomaly detection, automated incident response, and predictive cyber defense. Despite remarkable advances in machine learning, deep learning, and generative AI, many AI-driven cybersecurity solutions operate as "black-box" models, making it difficult for security analysts to understand, verify, and trust their decisions. The lack of transparency and interpretability can hinder effective incident response, regulatory compliance, risk assessment, and operational decision-making. Explainable Artificial Intelligence (XAI) addresses these challenges by providing transparent, interpretable, and accountable AI models that enable cybersecurity professionals to understand how and why AI systems generate predictions, alerts, and recommendations.

The International Conference on Cyber Security in Artificial Intelligence (ICCSAI 2027) invites original research contributions on Explainable AI for Security Operations. This track provides an interdisciplinary platform for researchers, cybersecurity practitioners, AI experts, SOC analysts, industry professionals, and policymakers to present innovative research and practical solutions that integrate explainability into AI-powered security operations. Contributions addressing interpretable threat detection, transparent intrusion detection systems, explainable malware analysis, AI-assisted digital forensics, trustworthy automation, human-AI collaboration, fairness, accountability, and regulatory compliance are highly encouraged.

1. Explainable AI Foundations

• Explainable Artificial Intelligence (XAI)

• Interpretable Machine Learning for Cybersecurity

• Transparent AI Models

• Human-Centered Explainable AI

• Causality and Explainability in AI

• Explainability Metrics and Evaluation

2. Explainable Threat Detection

• Explainable Intrusion Detection Systems (IDS)

• Explainable Intrusion Prevention Systems (IPS)

• Explainable Anomaly Detection

• Explainable Threat Hunting

• Explainable User and Entity Behavior Analytics (UEBA)

• AI-Assisted Threat Attribution

3. Explainable Malware Analysis

• Explainable Malware Detection

• Explainable Malware Classification

• Explainable Ransomware Detection

• AI-Based Reverse Engineering

• Explainable Malware Behavior Analysis

• Explainable Fileless Malware Detection

4. Explainable Security Operations

• Explainable Security Operations Centers (SOC)

• Explainable Security Information and Event Management (SIEM)

• Explainable Security Orchestration, Automation, and Response (SOAR)

• AI-Assisted Incident Response

• Explainable Alert Prioritization

• Explainable Security Analytics

5. Explainable AI for Network and Cloud Security

• Explainable Network Traffic Analysis

• Explainable Cloud Security Analytics

• Explainable Zero Trust Security

• Explainable Cloud Threat Detection

• Explainable API Security

• Explainable Software-Defined Networking (SDN) Security

6. Explainable AI for Emerging Technologies

• Explainable Large Language Models (LLMs) for Cybersecurity

• Explainable Generative AI for Security

• Explainable AI for IoT Security

• Explainable AI for Edge Computing Security

• Explainable AI for Industrial Control Systems (ICS)

• Explainable AI for Critical Infrastructure Protection

7. Trustworthy and Responsible AI

• Trustworthy AI for Security Operations

• Fairness and Bias in Cybersecurity AI

• AI Accountability and Transparency

• Human-AI Collaboration in Security Operations

• Responsible AI for Cyber Defense

• AI Governance and Ethics

8. Robustness and Adversarial Explainability

• Adversarial Machine Learning

• Explainability Under Adversarial Attacks

• Robust Explainable AI Models

• Explainable AI for Model Poisoning Detection

• Explainable AI for Evasion Attack Detection

• Secure Explainability Techniques

9. Privacy and Compliance

• Privacy-Preserving Explainable AI

• Explainability for Regulatory Compliance

• Explainable AI Auditing

• AI Risk Assessment and Compliance

• Explainable Data Governance

• Secure AI Decision Logging

10. Visualization and Decision Support

• Visual Analytics for Cybersecurity

• Interactive Explainability Dashboards

• Explainable Threat Intelligence Visualization

• Explainable Security Decision Support Systems

• Explainable Cyber Risk Analytics

• AI-Assisted Security Reporting

11. Evaluation and Benchmarking

• Explainability Evaluation Frameworks

• Benchmarking Explainable AI for Security

• Performance–Interpretability Trade-offs

• Validation of Explainable Security Models

• Security Datasets for Explainable AI

• Human-Centered Evaluation of XAI

12. Future Directions

• Autonomous Explainable Security Systems

• Explainable AI Agents for Cyber Defense

• Federated Explainable AI

• Multi-Agent Explainable Security

• Explainable AI for Quantum-Safe Security

• Digital Twins for Explainable Cybersecurity

• Explainable AI for Security Automation

• Case Studies and Industrial Applications