[HTML][HTML] A new two-phase intrusion detection system with Naïve Bayes machine learning for data classification and elliptic envelop method for anomaly detection
M Vishwakarma, N Kesswani - Decision Analytics Journal, 2023 - Elsevier
Technology is pivotal in the rapid growth of services and intensifying the quality of life.
Recent technology, like the Internet of Things (IoT), demonstrates an impressive …
Recent technology, like the Internet of Things (IoT), demonstrates an impressive …
TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system
Intrusion detection systems (IDSs) play a pivotal role in computer security by discovering
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
[PDF][PDF] Anomaly-based intrusion detection through k-means clustering and naives bayes classification
Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying
intrusive activities on a computer system, and their enhancement is emerging at an …
intrusive activities on a computer system, and their enhancement is emerging at an …
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
S Aljawarneh, M Aldwairi, MB Yassein - Journal of Computational Science, 2018 - Elsevier
Efficiently detecting network intrusions requires the gathering of sensitive information. This
means that one has to collect large amounts of network transactions including high details of …
means that one has to collect large amounts of network transactions including high details of …
M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning
AV Turukmane, R Devendiran - Computers & Security, 2024 - Elsevier
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …
Ensemble and deep-learning methods for two-class and multi-attack anomaly intrusion detection: an empirical study
Cyber-security, as an emerging field of research, involves the development and
management of techniques and technologies for protection of data, information and devices …
management of techniques and technologies for protection of data, information and devices …
A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets
The widespread acceptance and increase of the Internet and mobile technologies have
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
An ensemble of prediction and learning mechanism for improving accuracy of anomaly detection in network intrusion environments
The connectivity of our surrounding objects to the internet plays a tremendous role in our
daily lives. Many network applications have been developed in every domain of life …
daily lives. Many network applications have been developed in every domain of life …
A hybrid anomaly classification with deep learning (DL) and binary algorithms (BA) as optimizer in the intrusion detection system (IDS)
Nowadays, along with network development, due to the threats of unknown sources,
information communication is more vulnerable, and thus, more secured information is …
information communication is more vulnerable, and thus, more secured information is …
Intrusion detection using big data and deep learning techniques
In this paper, Big Data and Deep Learning Techniques are integrated to improve the
performance of intrusion detection systems. Three classifiers are used to classify network …
performance of intrusion detection systems. Three classifiers are used to classify network …