Researchers have developed GuardianAgent, a novel framework for anonymizing live web traffic that goes beyond simple detection of private data. This system assesses the risk of disclosure by considering policy violations, data sensitivity, and contextual factors, rather than relying solely on LLMs. GuardianAgent employs a multi-factor risk scoring formula (AMRSF) to determine whether to allow, transform, or deny outgoing actions, and it uses an adaptive rewriting hierarchy to ensure appropriate anonymization levels. Experiments demonstrate that GuardianAgent achieves a superior privacy-utility trade-off compared to existing methods across various benchmarks. AI
IMPACT Enhances privacy protection for web traffic by offering a more nuanced and adaptive approach to anonymization.
RANK_REASON The cluster contains a research paper detailing a new anonymization framework.
- AMRSF
- arXiv
- GuardianAgent
- Hugging Face
- PII-Masking-300k
- SynthPAI
- Tábor
- alphaXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- ScienceCast
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