Adversarial Learning: A Critical Review and Active Learning Study

27 May 2017

Papers citing "Adversarial Learning: A Critical Review and Active Learning Study"

7 / 7 papers shown

Title
Overcoming Adversarial Attacks for Human-in-the-Loop Applications Ryan McCoppin Marla Kennedy P. Lukyanenko Sean M. Kennedy AAML 39 1 0 09 Jun 2023
New data poison attacks on machine learning classifiers for mobile exfiltration M. A. Ramírez Sangyoung Yoon Ernesto Damiani H. A. Hamadi C. Ardagna Nicola Bena Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 52 4 0 20 Oct 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 30 37 0 21 Feb 2022
A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap? Nathan G. Drenkow Numair Sani I. Shpitser Mathias Unberath 21 75 0 01 Dec 2021
Backdoor Attack and Defense for Deep Regression Xi Li G. Kesidis David J. Miller V. Lucic AAML 19 6 0 06 Sep 2021
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 19 35 0 12 Apr 2019
IoT-KEEPER: Securing IoT Communications in Edge Networks I. Hafeez M. Antikainen Aaron Yi Ding Sasu Tarkoma 14 10 0 19 Oct 2018