I. INTRODUCTION  
A. Related Work  

II. OVERVIEW OF THE IOT SYSTEM  
A. Physical objects  
B. Connectivity  
C. Middleware  
D. Big Data Analytics  
E. Applications  
F. Collaboration and Business Objective  

III. IOT SECURITY THREATS  
A. Threats in IoT  
B. Attack Surfaces  

IV. REVIEW OF MACHINE LEARNING AND DEEP LEARNING APPLICATIONS IN IOT SECURITY  
A. Machine learning (ML) methods for IoT security  
B. Deep learning (DL) methods for IoT Security  
C. Reinforcement learning (RL) methods for IoT security  

V. IOT SECURITY LAYERS BASED ON ML AND DL METHODS  
A. Perception layer  
B. Network layer  
C. Application layer  
D. Enabling technology for ML/DL deployment for IoT security  

VI. ISSUES, CHALLENGES AND FUTURE DIRECTIONS  
A. IoT data related issues  
B. Learning Strategies for Effective IoT Security  
C. ML and DL for IoT security in interdependent, interconnected and interactive environments  
D. ML and DL Challenges  
E. Integrating DL/ML with Other Technology for IoT Security  
F. Computational complexity  
G. Security vs Trade-offs in IoT Applications  

VII. CONCLUSION