A review of federated learning in intrusion detection systems for iot
Intrusion detection systems are evolving into intelligent systems that perform data analysis
searching for anomalies in their environment. The development of deep learning …
searching for anomalies in their environment. The development of deep learning …
Detection of cyberattacks and anomalies in cyber-physical systems: Approaches, data sources, evaluation
O Tushkanova, D Levshun, A Branitskiy… - Algorithms, 2023 - mdpi.com
Cyberattacks on cyber-physical systems (CPS) can lead to severe consequences, and
therefore it is extremely important to detect them at early stages. However, there are several …
therefore it is extremely important to detect them at early stages. However, there are several …
Fed-anids: Federated learning for anomaly-based network intrusion detection systems
As computer networks and interconnected systems continue to gain widespread adoption,
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
ensuring cybersecurity has become a prominent concern for organizations, regardless of …
Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: A survey
S Ali, Q Li, A Yousafzai - Ad Hoc Networks, 2024 - Elsevier
The industrial internet of things (IIoT) is an evolutionary extension of the traditional Internet of
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
A federated feature selection algorithm based on particle swarm optimization under privacy protection
Y Hu, Y Zhang, X Gao, D Gong, X Song, Y Guo… - Knowledge-Based …, 2023 - Elsevier
Feature selection is an important preprocessing technique in the fields of data mining and
machine learning. With the promotion of privacy protection awareness, recently it becomes a …
machine learning. With the promotion of privacy protection awareness, recently it becomes a …
[HTML][HTML] Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover,
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …
Federated feature selection for horizontal federated learning in iot networks
Under horizontal federated learning (HFL) in the Internet of Things (IoT) scenarios, different
user data sets have significant similarities on the feature spaces, the final goal is to build a …
user data sets have significant similarities on the feature spaces, the final goal is to build a …
Vertical federated learning-based feature selection with non-overlapping sample utilization
S Feng - Expert Systems with Applications, 2022 - Elsevier
Vertical federated learning (VFL) is a privacy preserving collaborative machine learning
technique designed for distributed learning scenarios in which data from different parties …
technique designed for distributed learning scenarios in which data from different parties …
The evolution of federated learning-based intrusion detection and mitigation: a survey
In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
SIDS: A federated learning approach for intrusion detection in IoT using Social Internet of Things
Abstract The Internet of Things (IoT) ecosystem needs Intrusion Detection Systems (IDS) to
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …