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 review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …
academic field. The objective of IoT is to combine the physical environment with the cyber …
Explainable artificial intelligence (XAI) to enhance trust management in intrusion detection systems using decision tree model
Despite the growing popularity of machine learning models in the cyber‐security
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …
A comprehensive survey and taxonomy of the SVM-based intrusion detection systems
The increasing number of security attacks have inspired researchers to employ various
classifiers, such as support vector machines (SVMs), to deal with them in Intrusion detection …
classifiers, such as support vector machines (SVMs), to deal with them in Intrusion detection …
Network intrusion detection combined hybrid sampling with deep hierarchical network
K Jiang, W Wang, A Wang, H Wu - IEEE access, 2020 - ieeexplore.ieee.org
Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …
and preventing malicious activities. Due to the complex and time-varying network …
Hybrid intrusion detection using mapreduce based black widow optimized convolutional long short-term memory neural networks
PR Kanna, P Santhi - Expert Systems with Applications, 2022 - Elsevier
The recent advancements in information and communication technologies have led to an
increasing number of online systems and services. These online systems can utilize …
increasing number of online systems and services. These online systems can utilize …
Internet of Things: A survey on machine learning-based intrusion detection approaches
In the world scenario, concerns with security and privacy regarding computer networks are
always increasing. Computer security has become a necessity due to the proliferation of …
always increasing. Computer security has become a necessity due to the proliferation of …
Data-centric artificial intelligence: A survey
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …
of its great success is the availability of abundant and high-quality data for building machine …
An evolutionary SVM model for DDOS attack detection in software defined networks
Software-Defined Network (SDN) has become a promising network architecture in current
days that provide network operators more control over the network infrastructure. The …
days that provide network operators more control over the network infrastructure. The …
[HTML][HTML] An extended machine learning technique for polycystic ovary syndrome detection using ovary ultrasound image
Polycystic ovary syndrome (PCOS) is the most prevalent endocrinological abnormality and
one of the primary causes of anovulatory infertility in women globally. The detection of …
one of the primary causes of anovulatory infertility in women globally. The detection of …