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20182021
most citedPhishing Attacks and Websites Classification Using Machine Learning and Multiple Datasets (A Comparative Analysis)

35 citations · 35 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CR202135 cited

Phishing Attacks and Websites Classification Using Machine Learning and Multiple Datasets (A Comparative Analysis)

Sohail Ahmed Khan, Wasiq Khan, Abir Hussain

Phishing attacks are the most common type of cyber-attacks used to obtain sensitive information and have been affecting individuals as well as organisations across the globe. Vario…

cs.LG2020

Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching

Wasiq Khan, Abir Hussain, Sohail Ahmed Khan +3

Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 20201…

astro-ph.IM2018

GRAPE: Genetic Routine for Astronomical Period Estimation

Paul R. McWhirter, Iain A. Steele, Abir Hussain +2

Period estimation is an important task in the classification of many variable astrophysical objects. Here we present GRAPE: Genetic Routine for Astronomical Period Estimation, a ge…

q-bio.GN2018

Analysis of Extremely Obese Individuals Using Deep Learning Stacked Autoencoders and Genome-Wide Genetic Data

Casimiro A. Curbelo Montañez, Paul Fergus, Carl Chalmers +1

The aetiology of polygenic obesity is multifactorial, which indicates that life-style and environmental factors may influence multiples genes to aggravate this disorder. Several lo…

cs.CY2018

Deep Learning Classification of Polygenic Obesity using Genome Wide Association Study SNPs

Casimiro Adays Curbelo Montañez, Paul Fergus, Almudena Curbelo Montañez +1

In this paper, association results from genome-wide association studies (GWAS) are combined with a deep learning framework to test the predictive capacity of statistically signific…