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 …
Toward feasible machine learning model updates in network-based intrusion detection
Over the last years, several works have proposed highly accurate machine learning (ML)
techniques for network-based intrusion detection systems (NIDS), that are hardly used in …
techniques for network-based intrusion detection systems (NIDS), that are hardly used in …
Segmented federated learning for adaptive intrusion detection system
Cyberattacks are a major issues and it causes organizations great financial, and reputation
harm. However, due to various factors, the current network intrusion detection systems …
harm. However, due to various factors, the current network intrusion detection systems …
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 long-lasting reinforcement learning intrusion detection model
Several works have proposed highly accurate network-based intrusion detection schemes
through machine learning techniques. However, they are unable to address changes in …
through machine learning techniques. However, they are unable to address changes in …
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 …
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 for anomaly-based intrusion detection
MA Ayed, C Talhi - 2021 International Symposium on Networks …, 2021 - ieeexplore.ieee.org
We are attending a severe zero-day cyber attacks. Machine learning based anomaly
detection is definitely the most efficient defence in depth approach. It consists to analyzing …
detection is definitely the most efficient defence in depth approach. It consists to analyzing …
Facing the unknown: A stream learning intrusion detection system for reliable model updates
Current machine learning approaches for network-based intrusion detection do not cope
with new network traffic behavior, which requires periodic computationally and time …
with new network traffic behavior, which requires periodic computationally and time …
Reinforcement learning for intrusion detection: More model longness and fewer updates
Several works have used machine learning techniques for network-based intrusion
detection over the past few years. While proposed schemes have been able to provide high …
detection over the past few years. While proposed schemes have been able to provide high …