Showing cs.CRShow all
3 papers · 1 filter
cs.CR2025
A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives
Kaixiang Zhao, Lincan Li, Kaize Ding +3
Machine learning (ML) models have significantly grown in complexity and utility, driving advances across multiple domains. However, substantial computational resources and speciali…
cs.CR2025
A Survey on Model Extraction Attacks and Defenses for Large Language Models
Kaixiang Zhao, Lincan Li, Kaize Ding +3
Model extraction attacks pose significant security threats to deployed language models, potentially compromising intellectual property and user privacy. This survey provides a comp…
cs.CR2025
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
Kaixiang Zhao, Lincan Li, Kaize Ding +3
Model Extraction Attacks (MEAs) threaten modern machine learning systems by enabling adversaries to steal models, exposing intellectual property and training data. With the increas…