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 …
Intrusion Detection based on Federated Learning: a systematic review
JL Hernandez-Ramos, G Karopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
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 …
Federated learning for intrusion detection system: Concepts, challenges and future directions
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …
making its infrastructure more complex and heterogeneous. The predominated usage of …
[HTML][HTML] Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges
Abstract The application of Machine Learning (ML) techniques to the well-known intrusion
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
Comparative review of the intrusion detection systems based on federated learning: Advantages and open challenges
E Fedorchenko, E Novikova, A Shulepov - Algorithms, 2022 - mdpi.com
In order to provide an accurate and timely response to different types of the attacks, intrusion
and anomaly detection systems collect and analyze a lot of data that may include personal …
and anomaly detection systems collect and analyze a lot of data that may include personal …
[HTML][HTML] GöwFed: A novel federated network intrusion detection system
Network intrusion detection systems are evolving into intelligent systems that perform data
analysis while searching for anomalies in their environment. Indeed, the development of …
analysis while searching for anomalies in their environment. Indeed, the development of …
Federated learning for reliable model updates in network-based intrusion detection
Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
Adaptive intrusion detection in the networking of large-scale lans with segmented federated learning
Predominant network intrusion detection systems (NIDS) aim to identify malicious traffic
patterns based on a handcrafted dataset of rules. Recently, the application of machine …
patterns based on a handcrafted dataset of rules. Recently, the application of machine …
Federated learning-based network intrusion detection with a feature selection approach
Y Qin, M Kondo - 2021 International conference on electrical …, 2021 - ieeexplore.ieee.org
With the increase and diversity of network attacks, machine learning has shown its efficiency
in realizing intrusion detection. Federated Learning (FL) has been proposed as a new …
in realizing intrusion detection. Federated Learning (FL) has been proposed as a new …