AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work discusses how power-aware software applications and scheduling might be used to reduce power consumption, both as autonomous entities and as part of a (globally) distributed system.
This work expands upon the privacy threat assessment model to quantitatively evaluate the risks of data likability, identifiability, non-repudiation, detectability, unintended disclosure, indulgence, and policy & consent noncompliance, and constructs a framework aimed at mitigating these identified risks.
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