Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
A review of principal component analysis algorithm for dimensionality reduction
BMS Hasan, AM Abdulazeez - Journal of Soft Computing …, 2021 - publisher.uthm.edu.my
Big databases are increasingly widespread and are therefore hard to understand, in
exploratory biomedicine science, big data in health research is highly exciting because data …
exploratory biomedicine science, big data in health research is highly exciting because data …
A dependable hybrid machine learning model for network intrusion detection
Network intrusion detection systems (NIDSs) play an important role in computer network
security. There are several detection mechanisms where anomaly-based automated …
security. There are several detection mechanisms where anomaly-based automated …
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 …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …
involve many electronic control units connected through intravehicle networks (IVNs) to …
An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture
The entire computing paradigm is changed due to the technological advancements in
Information and Communication Technology (ICT). Due to these advancements, various …
Information and Communication Technology (ICT). Due to these advancements, various …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
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 …
Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms
YK Saheed, MO Arowolo - IEEE Access, 2021 - ieeexplore.ieee.org
Information and communication technology (ICT) advancements have altered the entire
computing paradigm. As a result of these improvements, numerous new channels of …
computing paradigm. As a result of these improvements, numerous new channels of …