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Full-Text Articles in Computer Sciences
A Gpu-Based Machine Learning Approach For Detection Of Botnet Attacks, Michal Motylinski, Áine Macdermott, Farkhund Iqbal, Babar Shah
A Gpu-Based Machine Learning Approach For Detection Of Botnet Attacks, Michal Motylinski, Áine Macdermott, Farkhund Iqbal, Babar Shah
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Rapid development and adaptation of the Internet of Things (IoT) has created new problems for securing these interconnected devices and networks. There are hundreds of thousands of IoT devices with underlying security vulnerabilities, such as insufficient device authentication/authorisation making them vulnerable to malware infection. IoT botnets are designed to grow and compete with one another over unsecure devices and networks. Once infected, the device will monitor a Command-and-Control (C&C) server indicating the target of an attack via Distributed Denial of Service (DDoS) attack. These security issues, coupled with the continued growth of IoT, presents a much larger attack surface for …
Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi
Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi
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COVID-19 detection from medical imaging is a difficult challenge that has piqued the interest of experts worldwide. Chest X-rays and computed tomography (CT) scanning are the essential imaging modalities for diagnosing COVID-19. All researchers focus their efforts on developing viable methods and rapid treatment procedures for this pandemic. Fast and accurate automated detection approaches have been devised to alleviate the need for medical professionals. Deep Learning (DL) technologies have successfully recognized COVID-19 situations. This paper proposes a developed set of nine deep learning models for diagnosing COVID-19 based on transfer learning and implementation in a novel architecture (SEL-COVIDNET). In which …
Studying The Role Of Cerebrovascular Changes In Different Compartments In Human Brains In Hypertension Prediction, Heba Kandil, Ahmed Soliman, Nada Elsaid, Ahmed Saied, Norah Saleh Alghamdi, Ali Mahmoud, Fatma Taher, Ayman El-Baz
Studying The Role Of Cerebrovascular Changes In Different Compartments In Human Brains In Hypertension Prediction, Heba Kandil, Ahmed Soliman, Nada Elsaid, Ahmed Saied, Norah Saleh Alghamdi, Ali Mahmoud, Fatma Taher, Ayman El-Baz
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Hypertension is a major cause of mortality of millions of people worldwide. Cerebral vascular changes are clinically observed to precede the onset of hypertension. The early detection and quantification of these cerebral changes would help greatly in the early prediction of the disease. Hence, preparing appropriate medical plans to avoid the disease and mitigate any adverse events. This study aims to investigate whether studying the cerebral changes in specific regions of human brains (specifically, the anterior, and the posterior compartments) separately, would increase the accuracy of hypertension prediction compared to studying the vascular changes occurring over the entire brain’s vasculature. …
Afnd: Arabic Fake News Dataset For The Detection And Classification Of Articles Credibility, Ashwaq Khalil, Moath Jarrah, Monther Aldwairi, Manar Jaradat
Afnd: Arabic Fake News Dataset For The Detection And Classification Of Articles Credibility, Ashwaq Khalil, Moath Jarrah, Monther Aldwairi, Manar Jaradat
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The news credibility detection task has started to gain more attention recently due to the rapid increase of news on different social media platforms. This article provides a large, labeled, and diverse Arabic Fake News Dataset (AFND) that is collected from public Arabic news websites. This dataset enables the research community to use supervised and unsupervised machine learning algorithms to classify the credibility of Arabic news articles. AFND consists of 606912 public news articles that were scraped from 134 public news websites of 19 different Arab countries over a 6-month period using Python scripts. The Arabic fact-check platform, Misbar, is …
Smart Covid-3d-Scnn: A Novel Method To Classify X-Ray Images Of Covid-19, Ahed Abugabah, Atif Mehmood, Ahmad Ali Al Zubi, Louis Sanzogni
Smart Covid-3d-Scnn: A Novel Method To Classify X-Ray Images Of Covid-19, Ahed Abugabah, Atif Mehmood, Ahmad Ali Al Zubi, Louis Sanzogni
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The outbreak of the novel coronavirus has spread worldwide, and millions of people are being infected. Image or detection classification is one of the first application areas of deep learning, which has a significant contribution to medical image analysis. In classification detection, one or more images (detection) are usually used as input, and diagnostic variables (such as whether there is a disease) are used as output. The novel coronavirus has spread across the world, infecting millions of people. Early-stage detection of critical cases of COVID-19 is essential. X-ray scans are used in clinical studies to diagnose COVID-19 and Pneumonia early. …