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#model-extraction News & Analysis

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

2 articles
AIBearisharXiv – CS AI · May 77/10
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On the (In-)Security of the Shuffling Defense in the Transformer Secure Inference

Researchers demonstrate that the shuffling defense mechanism used to protect Transformer model weights during secure inference can be broken through an alignment attack, allowing adversaries to recover weights with minimal cost. The attack exploits multiple shuffled activations by finding a common permutation, undermining a key security assumption in privacy-preserving machine learning.

AINeutralarXiv – CS AI · Jun 116/10
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T2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking

Researchers propose T2S, a rehearsal-based watermarking framework that protects AI models against extraction attacks by simulating the theft process during training. The method embeds watermarks that remain detectable even when adversaries steal and replicate models, addressing a critical vulnerability in AI intellectual property protection.