RobustFL: Robust federated learning against poisoning attacks in industrial IoT systems
Industrial Internet of Things (IIoT) systems are key enabling infrastructures that sustain the
functioning of production and manufacturing. To satisfy the intelligence demands, federated …
functioning of production and manufacturing. To satisfy the intelligence demands, federated …
SCA: Sybil-based collusion attacks of IIoT data poisoning in federated learning
With the massive amounts of data generated by industrial Internet of Things (IIoT) devices at
all moments, federated learning (FL) enables these distributed distrusted devices to …
all moments, federated learning (FL) enables these distributed distrusted devices to …
SPEFL: efficient security and privacy enhanced federated learning against poisoning attacks
Z Ke, L Shen, J Shi, X Zhang, Y Sun… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning paradigm in the Internet of Things
(IoT), which allows multiple devices to collaboratively train models without leaking local …
(IoT), which allows multiple devices to collaboratively train models without leaking local …
Multitentacle federated learning over software-defined industrial internet of things against adaptive poisoning attacks
G Li, J Wu, S Li, W Yang, C Li - IEEE Transactions on Industrial …, 2022 - ieeexplore.ieee.org
Software-defined industrial Internet of things (SD-IIoT) exploits federated learning to process
the sensitive data at edges, while adaptive poisoning attacks threat the security of SD-IIoT …
the sensitive data at edges, while adaptive poisoning attacks threat the security of SD-IIoT …
FDSFL: Filtering Defense Strategies toward Targeted Poisoning Attacks in IIoT-Based Federated Learning Networking System
As a novel distributed machine learning scheme, federated learning (FL) efficiently realizes
the collaborative training of models by global participants while also protecting their data …
the collaborative training of models by global participants while also protecting their data …
Federated learning-based intrusion detection in the context of IIoT networks: poisoning attack and defense
Abstract The emerging of Federated Learning (FL) paradigm in training has been drawn
much attention from research community because of the demand of privacy preservation in …
much attention from research community because of the demand of privacy preservation in …
PoisonGAN: Generative poisoning attacks against federated learning in edge computing systems
Edge computing is a key-enabling technology that meets continuously increasing
requirements for the intelligent Internet-of-Things (IoT) applications. To cope with the …
requirements for the intelligent Internet-of-Things (IoT) applications. To cope with the …
Detecting and mitigating poisoning attacks in federated learning using generative adversarial networks
In the age of the Internet of Things (IoT), large numbers of sensors and edge devices are
deployed in various application scenarios; Therefore, collaborative learning is widely used …
deployed in various application scenarios; Therefore, collaborative learning is widely used …
D2MIF: A malicious model detection mechanism for federated learning empowered artificial intelligence of things
Artificial Intelligence of Things (AIoT), as a fusion of artificial intelligence (AI) and Internet of
Things (IoT), has become a new trend to realize the intelligentization of industry 4.0 and the …
Things (IoT), has become a new trend to realize the intelligentization of industry 4.0 and the …
Secureiiot environment: Federated learning empowered approach for securing iiot from data breach
The growing congruence of gadgets today resulted in a numerous type of cyber attacks. A
similar trend occurs with the industrial Internet of Things (IIoT), wherein increasing data …
similar trend occurs with the industrial Internet of Things (IIoT), wherein increasing data …