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IEEE/ICACT20260343 Slide.17        [Big Slide]       [YouTube]	Oral Presentation
	Let¡¯s walk through the architecture. Component A is DID-based identity management, binding each entity to a stable identity to enable accountability. Component B is a multi-factor credit model computed from resolution and caching behavior. Component C is trust synchronization via a lightweight gossip protocol, so domains share trust views without a centralized database. Component D is federated learning detection, enabling collaborative detection of low-rate, cross-domain attacks without sharing raw traffic. Together, these components form a closed loop: identity and behavior lead to credit; credit guides policies; and federated learning enhances detection and feeds back into credit updates.

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