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The Cloudcast

LLM Security and Privacy

Mar 27, 2024
Sean Falconer, Head of Marketing & Developer Relations @ Skyflow, talks about LLM security and privacy, preventing PII leaks. They delve into the challenges, fears of customer PII exposure, and leaking company IP. Discussions include the importance of data masking, governance, and compliance in ML lifecycle management. They also touch on data tokenization, API security, and de-identifying data for protection.
26:09

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Balancing security and privacy in LLMs involves making data usable without compromising privacy.
  • Implementing de-identification techniques like tokenization and depersonalization is crucial for safeguarding customer data.

Deep dives

LLM Security and Privacy Challenges

LLM security and privacy pose significant challenges due to the complexity of handling personally identifiable information (PII) in the context of AI. The balance between security and privacy becomes crucial as securing data involves not just blocking access but also making data usable without compromising privacy. The shift from traditional databases to AI models like deep learning and neural networks creates difficulties in managing and protecting PII, lacking practical deletion methods for data within AI models.

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