[HTML][HTML] Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications
Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine
Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments …
Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments …
Untargeted white-box adversarial attack with heuristic defence methods in real-time deep learning based network intrusion detection system
Abstract Network Intrusion Detection System (NIDS) is a key component in securing the
computer network from various cyber security threats and network attacks. However …
computer network from various cyber security threats and network attacks. However …
Adversarial Training: A Survey
Noisy-defense variational auto-encoder (ND-VAE): An adversarial defense framework to eliminate adversarial attacks
S Jalalipour, B Rekabdar - 2023 Fifth International Conference …, 2023 - ieeexplore.ieee.org
This paper presents a robust adversarial defense mechanism, Noisy-Defense Variational
Auto-Encoder (ND-VAE), that combines the strengths of Nouveau VAE (NVAE) and Defense …
Auto-Encoder (ND-VAE), that combines the strengths of Nouveau VAE (NVAE) and Defense …
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
In today's data-driven landscape, the delicate equilibrium between safeguarding user
privacy and unleashing data potential stands as a paramount concern. Federated learning …
privacy and unleashing data potential stands as a paramount concern. Federated learning …
Improving Machine Learning Robustness via Adversarial Training
L Dang, T Hapuarachchi, K **ong… - 2023 32nd International …, 2023 - ieeexplore.ieee.org
As Machine Learning (ML) is increasingly used in solving various tasks in real-world
applications, it is crucial to ensure that ML algorithms are robust to any potential worst-case …
applications, it is crucial to ensure that ML algorithms are robust to any potential worst-case …
Verifiable federated learning
In Federated Learning (FL) a significant body of research has focused on defending against
malicious clients. However, clients are not the only party that can behave maliciously. The …
malicious clients. However, clients are not the only party that can behave maliciously. The …