◕ Track1: Frontiers, Systems, and Security in Machine Learning

Generative Models
Graph Neural Networks
Deep Reinforcement Learning
Meta-Learning and Automated Machine Learning
Multimodal Learning and Transfer Learning
Model Architecture and Optimization Algorithms
Distributed and Parallel Computing Systems
Model Compression and Hardware Acceleration
Interpretability and Causal Inference
Adversarial and Privacy-Preserving Machine Learning
Federated Learning and Secure Aggregation
Online and Continual Learning

◕ Track 2: Data Security, Privacy Computing, and System Security

Applied Cryptography and Post-Quantum Cryptography
Data Privacy Models, Metrics, and Enhancement Techniques
Software and System Security
Supply Chain Security
Cyber Attacks and Intrusion Defense
Confidential Computing and Trusted Computing
Data Encryption and Secure Multi-Party Computation
Data Security Auditing and Risk Assessment
Internet of Things and Edge Computing Security
Cloud-Native Security

◕ Track 3: Intelligent Security Systems and Applications

Privacy Protection for Medical and Health Data
Smart Cities and Public Safety Monitoring
Industrial Internet Security and Anomaly Detection
Autonomous Driving Safety and Reliable Decision-Making
Cybersecurity Situational Awareness and Threat Intelligence
Digital Identity Authentication and Biometric Protection
Sustainable Security and Green Data Computing
Emergency Response and Automated Attack-Defense Systems