MLTs-ADCNs: Machine learning techniques for anomaly detection in communication networks
From a security perspective, the research of the jeopardized 6G wireless communications
and its expected ultra-densified ubiquitous wireless networks urge the development of a …
and its expected ultra-densified ubiquitous wireless networks urge the development of a …
Network anomaly uncovering on CICIDS-2017 dataset: a supervised artificial intelligence approach
P Jairu, AB Mailewa - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
In today's world, businesses and services are shifted to a digital transformation. As a result,
network traffic has tremendously increased over the years. With that, network threats and …
network traffic has tremendously increased over the years. With that, network threats and …
Comparing the performance of adaptive boosted classifiers in anomaly based intrusion detection system for networks
S Sivanantham, R Abirami… - … Conference on Vision …, 2019 - ieeexplore.ieee.org
The computer network is used by billions of people worldwide for variety of purposes. This
has made the security increasingly important in networks. It is essential to use Intrusion …
has made the security increasingly important in networks. It is essential to use Intrusion …
Hybrid machine learning for network anomaly intrusion detection
In this paper, a hybrid approach of combing two machine learning algorithms is proposed to
detect the different possible attacks by performing effective feature selection and …
detect the different possible attacks by performing effective feature selection and …
Anomaly detection in 6G networks using machine learning methods
While the cloudification of networks with a micro-services-oriented design is a well-known
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
Enhanced network anomaly detection based on deep neural networks
Due to the monumental growth of Internet applications in the last decade, the need for
security of information network has increased manifolds. As a primary defense of network …
security of information network has increased manifolds. As a primary defense of network …
A practical comparison of deep learning methods for network intrusion detection
TH Hai, LH Nam - 2021 International Conference on Electrical …, 2021 - ieeexplore.ieee.org
Cybersecurity is essential nowadays due to the vast development of Internet leading to
miscellaneous attacks to the cyber systems. Numerous measures have been proposed to …
miscellaneous attacks to the cyber systems. Numerous measures have been proposed to …
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 …
Detecting intrusions and attacks in the network traffic using anomaly based techniques
V Kumar, V Choudhary, V Sahrawat… - 2020 5th International …, 2020 - ieeexplore.ieee.org
Technology has become the backbone of today's Information and Communication
Technology. Today a large number of transactions are carried out online and thus possess a …
Technology. Today a large number of transactions are carried out online and thus possess a …
Anomaly analysis for the classification purpose of intrusion detection system with K-nearest neighbors and deep neural network
Nowadays, along with network development, due to the threats of unknown sources,
information communication is more vulnerable and require more secured information. An …
information communication is more vulnerable and require more secured information. An …