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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 …
Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Wrapper feature selection method based differential evolution and extreme learning machine for intrusion detection system
The intrusion detection system (IDS) has gained a rapid increase of interest due to its widely
recognized potential in various security fields, however, it suffers from several challenges …
recognized potential in various security fields, however, it suffers from several challenges …
Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
A machine learning security framework for iot systems
Internet of Things security is attracting a growing attention from both academic and industry
communities. Indeed, IoT devices are prone to various security attacks varying from Denial …
communities. Indeed, IoT devices are prone to various security attacks varying from Denial …
Using machine learning algorithms to enhance IoT system security
Abstract The term “Internet of Things”(IoT) refers to a system of networked computing
devices that may work and communicate with one another without direct human intervention …
devices that may work and communicate with one another without direct human intervention …
A taxonomy of network threats and the effect of current datasets on intrusion detection systems
As the world moves towards being increasingly dependent on computers and automation,
building secure applications, systems and networks are some of the main challenges faced …
building secure applications, systems and networks are some of the main challenges faced …
Attack classification using feature selection techniques: a comparative study
The goal of securing a network is to protect the information flowing through the network and
to ensure the security of intellectual as well as sensitive data for the underlying application …
to ensure the security of intellectual as well as sensitive data for the underlying application …
A taxonomy of machine-learning-based intrusion detection systems for the internet of things: A survey
The Internet of Things (IoT) is an emerging technology that has earned a lot of research
attention and technical revolution in recent years. Significantly, IoT connects and integrates …
attention and technical revolution in recent years. Significantly, IoT connects and integrates …