Security and Safety Aspects of AI in Industry Applications
Authors: Hans Dermot Doran | Published: 2022-07-16
Training Protocol
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations
Authors: Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt | Published: 2022-06-13
A New Security Boundary of Component Differentially Challenged XOR PUFs Against Machine Learning Modeling Attacks
Authors: Gaoxiang Li, Khalid T. Mursi, Ahmad O. Aseeri, Mohammed S. Alkatheiri, Yu Zhuang | Published: 2022-06-02
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
A Blessing of Dimensionality in Membership Inference through Regularization
Authors: Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk | Published: 2022-05-27 | Updated: 2023-04-14
Secure Aggregation for Federated Learning in Flower
Authors: Kwing Hei Li, Pedro Porto Buarque de Gusmão, Daniel J. Beutel, Nicholas D. Lane | Published: 2022-05-12
A Framework for Verifiable and Auditable Federated Anomaly Detection
Authors: Gabriele Santin, Inna Skarbovsky, Fabiana Fournier, Bruno Lepri | Published: 2022-03-15
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining
Authors: Yi Liu, Lei Xu, Xingliang Yuan, Cong Wang, Bo Li | Published: 2022-03-14
SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service
Authors: Songlei Wang, Yifeng Zheng, Xiaohua Jia | Published: 2022-02-16 | Updated: 2023-01-31
Training Differentially Private Models with Secure Multiparty Computation
Authors: Sikha Pentyala, Davis Railsback, Ricardo Maia, Rafael Dowsley, David Melanson, Anderson Nascimento, Martine De Cock | Published: 2022-02-05 | Updated: 2022-09-01