Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …
education, home, vehicles, or healthcare. With the increase in the number of connected …
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 …
Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset
SM Kasongo, Y Sun - Journal of Big Data, 2020 - Springer
Computer networks intrusion detection systems (IDSs) and intrusion prevention systems
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …
Machine learning methods for cyber security intrusion detection: Datasets and comparative study
The increase in internet usage brings security problems with it. Malicious software can affect
the operation of the systems and disrupt data confidentiality due to the security gaps in the …
the operation of the systems and disrupt data confidentiality due to the security gaps in the …
Variational LSTM enhanced anomaly detection for industrial big data
With the increasing population of Industry 4.0, industrial big data (IBD) has become a hotly
discussed topic in digital and intelligent industry field. The security problem existing in the …
discussed topic in digital and intelligent industry field. The security problem existing in the …
An effective intrusion detection approach using SVM with naïve Bayes feature embedding
J Gu, S Lu - Computers & Security, 2021 - Elsevier
Network security has become increasingly important in recent decades, while intrusion
detection system plays a critical role in protecting it. Various machine learning techniques …
detection system plays a critical role in protecting it. Various machine learning techniques …
Siamese neural network based few-shot learning for anomaly detection in industrial cyber-physical systems
With the increasing population of Industry 4.0, both AI and smart techniques have been
applied and become hotly discussed topics in industrial cyber-physical systems (CPS) …
applied and become hotly discussed topics in industrial cyber-physical systems (CPS) …
Performance analysis of machine learning models for intrusion detection system using Gini Impurity-based Weighted Random Forest (GIWRF) feature selection …
To protect the network, resources, and sensitive data, the intrusion detection system (IDS)
has become a fundamental component of organizations that prevents cybercriminal …
has become a fundamental component of organizations that prevents cybercriminal …
An effective convolutional neural network based on SMOTE and Gaussian mixture model for intrusion detection in imbalanced dataset
H Zhang, L Huang, CQ Wu, Z Li - Computer Networks, 2020 - Elsevier
Abstract Network Intrusion Detection System (NIDS) is a key security device in modern
networks to detect malicious activities. However, the problem of imbalanced class …
networks to detect malicious activities. However, the problem of imbalanced class …