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"

8 / 8 papers shown

Title
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 32 32 0 24 Oct 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences Daryna Oliynyk Rudolf Mayer Andreas Rauber 54 106 0 16 Jun 2022
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 34 105 0 17 Jun 2021
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 39 78 0 18 Feb 2020
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 36 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 22 67 0 01 May 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 18 116 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 16 11 0 24 Mar 2018