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Why MemPrivacy?
Cloud agents typically send user messages to remote LLMs and store conversation traces in memory systems (e.g., Mem0, LangMem, Memobase) for long-term personalization. This creates a large privacy attack surface: plaintext prompts and logs may contain PII, medical/financial data, credentials cloud memory stores can leak via retrieval, prompt injection, inversion, or misconfiguration naïve mitigation (e.g., *** masking) destroys task semantics, harming retrieval and personalization Goal: reduce privacy leakage without sacrificing utility.
Paper page - MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud AgentsVideos
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