HODA: Hardness-Oriented Detection of Model Extraction Attacks
Author:
Affiliation:
1. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/10206/10319981/10266376.pdf?arnumber=10266376
Reference42 articles.
1. Stealing machine learning models via prediction APIs;Tramèr
2. Practical Black-Box Attacks against Machine Learning
3. PRADA: Protecting Against DNN Model Stealing Attacks
4. Knockoff Nets: Stealing Functionality of Black-Box Models
5. High accuracy and high fidelity extraction of neural networks;Jagielski
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Making models more secure: An efficient model stealing detection method;Computers and Electrical Engineering;2024-07
2. AugSteal: Advancing Model Steal With Data Augmentation in Active Learning Frameworks;IEEE Transactions on Information Forensics and Security;2024
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