I. INTRODUCTION
A. Paper Motivation
B. Our Contribution
C. Paper Outline
II. BACKGROUND
A. Beyond 5G
B. Explainable AI
C. XAI for B5G Security
D. Implementation
III. B5G THREAT MODELLING AND TAXONOMY
A. Perception layer threats
B. Core/edge network layer threats
C. Service/Application layer threats
IV. ROLE OF XAI ON SECURITY ISSUES OF PERCEPTION LAYER
A. Security of B5G devices/IoT
B. Security of Radio Access Network
C. Security of B5G Edge Network
D. Security of Core and Backhaul Networks
VI. ROLE OF XAI ON SECURITY ISSUES OF CROSS LAYER ASPECTS
A. Security of B5G E2E Slicing
B. Security of B5G Network Automation/ZSM
VII. ROLE OF XAI ON OTHER SECURITY ENABLERS IN B5G
A. XAI in traditional Security methods
B. XAI and encryption methods
C. XAI and Federated Learning
D. Summary
VIII. USE-CASES IN XAI FOR B5G SECURITY - SERVICE LAYER
A. Smart Cities
B. Healthcare
C. Industry 4.0/5.0
D. Smart Grid 2.0
E. Extended Reality (XR)
F. Other Applications
IX. NEW SECURITY ISSUES AND CHALLENGES OF B5G DUE TO XAI
A. Increased vulnerability to adversarial ML attacks
B. New attack vector and target
C. Challenge to design secure ML applications with XAI
X. XAI B5G SECURITY PROJECTS AND STANDARDIZATION
A. Research Projects
B. Standardization related to AI security
XI. LESSONS LEARNED AND FUTURE RESEARCH DIRECTIONS
A. Role of XAI for B5G Security
B. Security issues of XAI in B5G
C. XAI for the Security of B5G Use Cases
D. Research projects and standards
XII. CONCLUSION