#privacy-attack News & Analysis

2 articles tagged with #privacy-attack. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBearisharXiv – CS AI · May 117/10

🧠

On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics

Researchers demonstrate significant privacy vulnerabilities in tabular diffusion models (TDMs), which are increasingly used to generate synthetic data as privacy-preserving alternatives. Through membership inference attacks in both black-box and white-box settings, the study reveals that attackers can successfully breach these systems without perfect knowledge of training data or massive computational resources, while also exposing flaws in commonly-used privacy metrics.

AIBearisharXiv – CS AI · Apr 147/10

🧠

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying

Researchers have developed ADAM, a novel privacy attack that exploits vulnerabilities in Large Language Model agents' memory systems through adaptive querying, achieving up to 100% success rates in extracting sensitive information. The attack highlights critical security gaps in modern LLM-based systems that rely on memory modules and retrieval-augmented generation, underscoring the urgent need for privacy-preserving safeguards.