2 papers
cs.LG2024
An Empirical Analysis of Federated Learning Models Subject to Label-Flipping Adversarial Attack
Kunal Bhatnagar, Sagana Chattanathan, Angela Dang +6
In this paper, we empirically analyze adversarial attacks on selected federated learning models. The specific learning models considered are Multinominal Logistic Regression (MLR),…
cs.LG2023
On the Steganographic Capacity of Selected Learning Models
Rishit Agrawal, Kelvin Jou, Tanush Obili +6
Machine learning and deep learning models are potential vectors for various attack scenarios. For example, previous research has shown that malware can be hidden in deep learning m…