AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Many machine learning applications involve sensitive data and therefore require training under differential privacy (DP). However, DP training often degrades model utility. In some cases, first pre-training the model on"public"data before finetuning with DP on the sensitive data can reduce the drop in utility. However,...
This work formalizes rigorous cryptographic security notions tailored to CMC frameworks, introduces a generic protocol template, and proves that it satisfies these requirements, which offer both cautionary evidence about existing approaches and constructive guidance for designing secure, privacy-preserving ML auditing...
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