Towards Understanding the Dynamics of the First-Order Adversaries
Authors: Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su | Published: 2020-10-20
Literature Database
Mitigating Sybil Attacks on Differential Privacy based Federated Learning
Authors: Yupeng Jiang, Yong Li, Yipeng Zhou, Xi Zheng | Published: 2020-10-20
Tight Second-Order Certificates for Randomized Smoothing
Authors: Alexander Levine, Aounon Kumar, Thomas Goldstein, Soheil Feizi | Published: 2020-10-20 | Updated: 2020-12-15
Image Obfuscation for Privacy-Preserving Machine Learning
Authors: Mathilde Raynal, Radhakrishna Achanta, Mathias Humbert | Published: 2020-10-20
A Survey of Machine Learning Techniques in Adversarial Image Forensics
Authors: Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo | Published: 2020-10-19
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification
Authors: Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck | Published: 2020-10-19
Dos and Don’ts of Machine Learning in Computer Security
Authors: Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck | Published: 2020-10-19 | Updated: 2021-11-30
Privacy-preserving Data Sharing on Vertically Partitioned Data
Authors: Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela | Published: 2020-10-19 | Updated: 2022-09-02
Taking Over the Stock Market: Adversarial Perturbations Against Algorithmic Traders
Authors: Elior Nehemya, Yael Mathov, Asaf Shabtai, Yuval Elovici | Published: 2020-10-19 | Updated: 2021-09-02
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization
Authors: Pranav Subramani, Nicholas Vadivelu, Gautam Kamath | Published: 2020-10-18 | Updated: 2021-10-26