Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains

23 March 2017

Papers citing "Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains"

20 / 20 papers shown

Title
Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks Satwik Kundu Debarshi Kundu Swaroop Ghosh AAML 56 5 0 18 Feb 2024
Understanding Overfitting in Adversarial Training via Kernel Regression Teng Zhang Kang Li 56 2 0 13 Apr 2023
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses Adnan Qayyum M. A. Butt Hassan Ali Muhammad Usman O. Halabi Ala I. Al-Fuqaha Q. Abbasi Muhammad Ali Imran Junaid Qadir 84 37 0 24 Oct 2022
A Framework for Understanding Model Extraction Attack and Defense Xun Xian Min-Fong Hong Jie Ding SILM MIACV FedML 37 2 0 23 Jun 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences Daryna Oliynyk Rudolf Mayer Andreas Rauber 114 114 0 16 Jun 2022
Exploring Adversarial Examples for Efficient Active Learning in Machine Learning Classifiers H. Yu Shihfeng Zeng Teng Zhang Ing-Chao Lin Yier Jin AAML 400 1 0 22 Sep 2021
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 102 109 0 17 Jun 2021
Imitation Privacy Xun Xian Xinran Wang Mingyi Hong Jie Ding R. Ghanadan 53 3 0 30 Aug 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 85 12 0 05 Jul 2020
Adversarial Attacks for Multi-view Deep Models Xuli Sun Shiliang Sun AAML 29 0 0 19 Jun 2020
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps Zhichuang Sun Ruimin Sun Long Lu Alan Mislove 90 81 0 18 Feb 2020
A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks P. Dasgupta J. B. Collins AAML 40 43 0 04 Dec 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 64 11 0 17 Jul 2019
A framework for the extraction of Deep Neural Networks by leveraging public data Soham Pal Yash Gupta Aditya Shukla Aditya Kanade S. Shevade V. Ganapathy FedML MLAU MIACV 82 56 0 22 May 2019
POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm Jinyin Chen Mengmeng Su Shijing Shen Hui Xiong Haibin Zheng AAML 124 68 0 01 May 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 131 117 0 02 Apr 2019
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning Tegjyot Singh Sethi M. Kantardzic Lingyu Lyu Jiashun Chen AAML 102 11 0 24 Mar 2018
Handling Adversarial Concept Drift in Streaming Data Tegjyot Singh Sethi M. Kantardzic 37 59 0 24 Mar 2018
Denoising Dictionary Learning Against Adversarial Perturbations John Mitro D. Bridge Steven D. Prestwich AAML 34 5 0 07 Jan 2018
Adversarial Frontier Stitching for Remote Neural Network Watermarking Erwan Le Merrer P. Pérez Gilles Trédan MLAU AAML 86 342 0 06 Nov 2017