|
|
|
|
|
Sikha Bagui, Dustin Mink, Subhash Bagui, Sakthivel Subramaniam and Daniel Wallace
This study, focusing on identifying rare attacks in imbalanced network intrusion datasets, explored the effect of using different ratios of oversampled to undersampled data for binary classification. Two designs were compared: random undersampling before...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sikha S. Bagui, Dustin Mink, Subhash C. Bagui and Sakthivel Subramaniam
Machine Learning is widely used in cybersecurity for detecting network intrusions. Though network attacks are increasing steadily, the percentage of such attacks to actual network traffic is significantly less. And here lies the problem in training Machi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Md. Maniruzzaman, Jungpil Shin and Md. Al Mehedi Hasan
Attention deficit hyperactivity disorder (ADHD) is one of childhood?s most frequent neurobehavioral disorders. The purpose of this study is to: (i) extract the most prominent risk factors for children with ADHD; and (ii) propose a machine learning (ML)-b...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nikola Andelic, Sandi Baressi ?egota, Ivan Lorencin and Matko Glucina
Malicious websites are web locations that attempt to install malware, which is the general term for anything that will cause problems in computer operation, gather confidential information, or gain total control over the computer. In this paper, a novel ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Maya Hilda Lestari Louk and Bayu Adhi Tama
Classifier ensembles have been utilized in the industrial cybersecurity sector for many years. However, their efficacy and reliability for intrusion detection systems remain questionable in current research, owing to the particularly imbalanced data issu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Moussa Diallo, Shengwu Xiong, Eshete Derb Emiru, Awet Fesseha, Aminu Onimisi Abdulsalami and Mohamed Abd Elaziz
Classification algorithms have shown exceptional prediction results in the supervised learning area. These classification algorithms are not always efficient when it comes to real-life datasets due to class distributions. As a result, datasets for real-l...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nicholas Fiorentini and Massimo Losa
Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine learning algorithms for predicting crash severity have recently gained interest by the academic community, there is a significant trend towards neglecting the fact that...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mauricio Barrios, Miguel Jimeno, Pedro Villalba and Edgar Navarro
Metabolic Syndrome (MetS) is a set of risk factors that increase the probability of heart disease or even diabetes mellitus. The diagnosis of the pathology implies compliance with at least three of five risk factors. Doctors obtain two of those factors i...
ver más
|
|
|
|
|
|