From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
A survey of stealth malware attacks, mitigation measures, and steps toward autonomous open world solutions
As our professional, social, and financial existences become increasingly digitized and as
our government, healthcare, and military infrastructures rely more on computer technologies …
our government, healthcare, and military infrastructures rely more on computer technologies …
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 …
Effective intrusion detection system using XGBoost
SS Dhaliwal, AA Nahid, R Abbas - Information, 2018 - mdpi.com
As the world is on the verge of venturing into fifth-generation communication technology and
embracing concepts such as virtualization and cloudification, the most crucial aspect …
embracing concepts such as virtualization and cloudification, the most crucial aspect …
Flow-based network traffic generation using generative adversarial networks
Flow-based data sets are necessary for evaluating network-based intrusion detection
systems (NIDS). In this work, we propose a novel methodology for generating realistic flow …
systems (NIDS). In this work, we propose a novel methodology for generating realistic flow …
5g-nidd: A comprehensive network intrusion detection dataset generated over 5g wireless network
With a plethora of new connections, features, and services introduced, the 5th generation
(5G) wireless technology reflects the development of mobile communication networks and is …
(5G) wireless technology reflects the development of mobile communication networks and is …
Applying big data based deep learning system to intrusion detection
With vast amounts of data being generated daily and the ever increasing interconnectivity of
the world's internet infrastructures, a machine learning based Intrusion Detection Systems …
the world's internet infrastructures, a machine learning based Intrusion Detection Systems …
Datasets are not enough: Challenges in labeling network traffic
In contrast to previous surveys, the present work is not focused on reviewing the datasets
used in the network security field. The fact is that many of the available public labeled …
used in the network security field. The fact is that many of the available public labeled …
An analysis of recurrent neural networks for botnet detection behavior
A Botnet can be conceived as a group of compromised computers which can be controlled
remotely to execute coordinated attacks or commit fraudulent acts. The fact that Botnets keep …
remotely to execute coordinated attacks or commit fraudulent acts. The fact that Botnets keep …
Intrusion detection techniques for mobile cloud computing in heterogeneous 5G
Mobile cloud computing is applied in multiple industries to obtain cloud‐based services by
leveraging mobile technologies. With the development of the wireless networks, defending …
leveraging mobile technologies. With the development of the wireless networks, defending …