AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is demonstrated that FHE-enabled models remain susceptible to both evasion and backdoor attacks, underscoring the need for stronger defenses in encrypted ML systems.
This work presents a framework that reformulates HE-aware model design as a constrained neural architecture search problem, where the objective is to identify architectures that are both cryptographically feasible and computationally efficient while preserving task performance.
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