Deep Learning Defenses Against Adversarial Examples for Dynamic Risk Assessment
Authors: Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Ines Goicoechea-Telleria, Raul Orduna-Urrutia | Published: 2020-07-02
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
Authors: Nuria Rodríguez-Barroso, Goran Stipcich, Daniel Jiménez-López, José Antonio Ruiz-Millán, Eugenio Martínez-Cámara, Gerardo González-Seco, M. Victoria Luzón, Miguel Ángel Veganzones, Francisco Herrera | Published: 2020-07-02 | Updated: 2020-10-06
Robust and Accurate Authorship Attribution via Program Normalization
Authors: Yizhen Wang, Mohannad Alhanahnah, Ke Wang, Mihai Christodorescu, Somesh Jha | Published: 2020-07-01 | Updated: 2022-02-25
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
Authors: Samuel Henrique Silva, Peyman Najafirad | Published: 2020-07-01 | Updated: 2020-07-03
Multi-Task Variational Information Bottleneck
Authors: Weizhu Qian, Bowei Chen, Yichao Zhang, Guanghui Wen, Franck Gechter | Published: 2020-07-01 | Updated: 2021-03-01
A Le Cam Type Bound for Adversarial Learning and Applications
Authors: Qiuling Xu, Kevin Bello, Jean Honorio | Published: 2020-07-01 | Updated: 2021-02-10
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection
Authors: Deqiang Li, Qianmu Li | Published: 2020-06-30
Model-Targeted Poisoning Attacks with Provable Convergence
Authors: Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian | Published: 2020-06-30 | Updated: 2021-04-21
Reducing Risk of Model Inversion Using Privacy-Guided Training
Authors: Abigail Goldsteen, Gilad Ezov, Ariel Farkash | Published: 2020-06-29
FDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
Authors: Yunfei Song, Tian Liu, Tongquan Wei, Xiangfeng Wang, Zhe Tao, Mingsong Chen | Published: 2020-06-28