Styx integrates sticky policies with TEEs to enforce data-specific rules throughout the full lifecycle in multi-party collaborative computing.
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3 Pith papers cite this work. Polarity classification is still indexing.
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PrivUn shows privacy unlearning in LLMs produces gradient-driven ripple effects and only shallow forgetting across layers, with new strategies proposed for deeper removal.
Only 0.4% of 1,000 Android apps show consistent alignment between their privacy policies and actual log contents, while 67.6% leak sensitive information not mentioned in policies.
citing papers explorer
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Styx: Collaborative and Private Data Processing With TEE-Enforced Sticky Policy
Styx integrates sticky policies with TEEs to enforce data-specific rules throughout the full lifecycle in multi-party collaborative computing.
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PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning
PrivUn shows privacy unlearning in LLMs produces gradient-driven ripple effects and only shallow forgetting across layers, with new strategies proposed for deeper removal.
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Do Privacy Policies Match with the Logs? An Empirical Study of Privacy Disclosure in Android Application Logs
Only 0.4% of 1,000 Android apps show consistent alignment between their privacy policies and actual log contents, while 67.6% leak sensitive information not mentioned in policies.