DualCF: Efficient Model Extraction Attack from Counterfactual Explanations

13 May 2022

Papers citing "DualCF: Efficient Model Extraction Attack from Counterfactual Explanations"

21 / 21 papers shown

Title
On the interplay of Explainability, Privacy and Predictive Performance with Explanation-assisted Model Extraction Fatima Ezzeddine Rinad Akel Ihab Sbeity Silvia Giordano Marc Langheinrich Omran Ayoub SILM 39 0 0 13 May 2025
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review Sonal Allana Mohan Kankanhalli Rozita Dara 35 0 0 05 May 2025
From Counterfactuals to Trees: Competitive Analysis of Model Extraction Attacks Awa Khouna Julien Ferry Thibaut Vidal AAML 54 0 0 07 Feb 2025
Private Counterfactual Retrieval With Immutable Features S. Meel Pasan Dissanayake M. Nomeir Sanghamitra Dutta S. Ulukus OffRL 33 0 0 15 Nov 2024
Efficient Model Extraction via Boundary Sampling Maor Biton Dor Yisroel Mirsky MLAU MIACV AAML 32 0 0 20 Oct 2024
Private Counterfactual Retrieval M. Nomeir Pasan Dissanayake S. Meel Sanghamitra Dutta S. Ulukus 29 1 0 17 Oct 2024
Privacy Implications of Explainable AI in Data-Driven Systems Fatima Ezzeddine 29 3 0 22 Jun 2024
AI Risk Management Should Incorporate Both Safety and Security Xiangyu Qi Yangsibo Huang Yi Zeng Edoardo Debenedetti Jonas Geiping ... Chaowei Xiao Bo Li Dawn Song Peter Henderson Prateek Mittal AAML 56 11 0 29 May 2024
Watermarking Counterfactual Explanations Hangzhi Guo Amulya Yadav AAML 48 0 0 29 May 2024
Model Reconstruction Using Counterfactual Explanations: Mitigating the Decision Boundary Shift Pasan Dissanayake Sanghamitra Dutta 59 6 0 08 May 2024
Knowledge Distillation-Based Model Extraction Attack using Private Counterfactual Explanations Fatima Ezzeddine Omran Ayoub Silvia Giordano AAML MIACV 45 0 0 04 Apr 2024
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures Thanh Tam Nguyen T. T. Huynh Zhao Ren Thanh Toan Nguyen Phi Le Nguyen Hongzhi Yin Quoc Viet Hung Nguyen 83 8 0 31 Mar 2024
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures S. V. Dibbo Adam Breuer Juston S. Moore Michael Teti AAML 46 4 0 21 Mar 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 31 5 0 22 Dec 2023
Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity Zhihao Zhu Chenwang Wu Rui Fan Yi Yang Defu Lian Enhong Chen AAML 33 0 0 18 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 52 2 0 07 Dec 2023
FDINet: Protecting against DNN Model Extraction via Feature Distortion Index Hongwei Yao Zheng Li Haiqin Weng Feng Xue Kui Ren Zhan Qin 43 4 0 20 Jun 2023
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models Abdullah Çaglar Öksüz Anisa Halimi Erman Ayday ELM AAML 23 2 0 04 Feb 2023
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences Daryna Oliynyk Rudolf Mayer Andreas Rauber 57 106 0 16 Jun 2022
MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI T. Miura Satoshi Hasegawa Toshiki Shibahara SILM MIACV 29 37 0 19 Jul 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 26 164 0 20 Oct 2020