Rieger, Phillip

DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection

Rieger, P., Nguyen, T. D., Miettinen, M., & Sadeghi, A.-R. (2022) · Proceedings 2022 Network and Distributed System Security Symposium

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 202

Poisoning Attacks on Federated Learning-based IoT Intrusion Detection System

Nguyen, T. D., Rieger, P., Miettinen, M., & Sadeghi, A.-R. (2020) · Proceedings 2020 Workshop on Decentralized IoT Systems and Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 200

BayBFed: Bayesian Backdoor Defense for Federated Learning

Kumari, K., Rieger, P., Fereidooni, H., Jadliwala, M., & Sadeghi, A.-R. (2023) · 2023 IEEE Symposium on Security and Privacy (SP)

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 37

CrowdGuard: Federated Backdoor Detection in Federated Learning

Rieger, P., Krauß, T., Miettinen, M., Dmitrienko, A., & Sadeghi, A.-R. (2024) · Proceedings 2024 Network and Distributed System Security Symposium

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 36