Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives

3 July 2023

Papers citing "Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives"

7 / 7 papers shown

Title
Adaptive Stress Testing for Adversarial Learning in a Financial Environment K. El-Awady AAML 19 2 0 08 Jul 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 92 72 0 20 Jan 2021
Adversarial Concept Drift Detection under Poisoning Attacks for Robust Data Stream Mining Lukasz Korycki Bartosz Krawczyk AAML 105 23 0 20 Sep 2020
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 69 457 0 03 Jul 2018
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 59 639 0 13 Sep 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 183 8,513 0 16 Aug 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 204 14,831 1 21 Dec 2013