[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions
N Moustafa, N Koroniotis, M Keshk… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research
attention in recent years, aiming to provide interpretability and confidence to the inner …
attention in recent years, aiming to provide interpretability and confidence to the inner …
A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …
between different communicating devices. The data should be communicated securely …
A survey of network-based intrusion detection data sets
Labeled data sets are necessary to train and evaluate anomaly-based network intrusion
detection systems. This work provides a focused literature survey of data sets for network …
detection systems. This work provides a focused literature survey of data sets for network …
A review of recent approaches on wrapper feature selection for intrusion detection
In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …
techniques for attack detection and classification, applied in intrusion detection area. Due to …
Application of deep reinforcement learning to intrusion detection for supervised problems
M Lopez-Martin, B Carro… - Expert Systems with …, 2020 - Elsevier
The application of new techniques to increase the performance of intrusion detection
systems is crucial in modern data networks with a growing threat of cyber-attacks. These …
systems is crucial in modern data networks with a growing threat of cyber-attacks. These …
An explainable machine learning framework for intrusion detection systems
M Wang, K Zheng, Y Yang, X Wang - IEEE Access, 2020 - ieeexplore.ieee.org
In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …
be effective; especially, deep neural networks improve the detection rates of intrusion …
Supervised feature selection techniques in network intrusion detection: A critical review
Abstract Machine Learning (ML) techniques are becoming an invaluable support for network
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …
A distributed ensemble design based intrusion detection system using fog computing to protect the internet of things networks
With the development of internet of things (IoT), capabilities of computing, networking
infrastructure, storage of data and management have come very close to the edge of …
infrastructure, storage of data and management have come very close to the edge of …
A Distributed framework for detecting DDoS attacks in smart contract‐based Blockchain‐IoT Systems by leveraging Fog computing
With the advancement of blockchain technology, and the proliferation of Internet of things
(IoT)‐driven devices, the blockchain‐IoT applications is changing the perception and …
(IoT)‐driven devices, the blockchain‐IoT applications is changing the perception and …