In this talk , I will talk about privacy risks with Machine Learning and explain in detail about Privacy Preserving Machine Learning techqniues. Introudce variious frameworks which can be used to implement to protect ML Models, Training Data, Inference Results from privacy threats. Talk about privacy threats in Large Lanauge Models ( LLM’s) and varous benchmarks in ML with resepct to privacy preserving and end the talk with a use case to protect the privacy threats in ML from internal attacks/in-memory attcks.
https://www.amazon.com/Privacy-Preserving-Machine-Learning-approach-pipelines-ebook/dp/B0BJ5RFVJC
{{ gettext('Login to leave a comment') }}
{{ gettext('Post a comment…') }}{{ errorMsg }}
{{ gettext('No comments posted yet') }}