I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
Authors: Daryna Oliynyk, Rudolf Mayer, Andreas Rauber | Published: 2022-06-16 | Updated: 2023-06-06
Poisoning
Deep Leakage from Model in Federated Learning
Authors: Zihao Zhao, Mengen Luo, Wenbo Ding | Published: 2022-06-10
Gradient Obfuscation Gives a False Sense of Security in Federated Learning
Authors: Kai Yue, Richeng Jin, Chau-Wai Wong, Dror Baron, Huaiyu Dai | Published: 2022-06-08 | Updated: 2022-10-14
Group privacy for personalized federated learning
Authors: Filippo Galli, Sayan Biswas, Kangsoo Jung, Tommaso Cucinotta, Catuscia Palamidessi | Published: 2022-06-07 | Updated: 2022-09-04
Building Robust Ensembles via Margin Boosting
Authors: Dinghuai Zhang, Hongyang Zhang, Aaron Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala | Published: 2022-06-07
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning
Authors: Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Zhongliang Yang, Yongfeng Huang, Xing Xie | Published: 2022-06-07 | Updated: 2022-10-31
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Authors: Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang | Published: 2022-06-01
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data
Authors: Huancheng Chen, Haris Vikalo | Published: 2022-06-01 | Updated: 2023-04-20
Differential Privacy: What is all the noise about?
Authors: Roxana Danger | Published: 2022-05-19
Representation learning with function call graph transformations for malware open set recognition
Authors: Jingyun Jia, Philip K. Chan | Published: 2022-05-13 | Updated: 2022-07-12