Ensemble machine learning paradigms in software defect prediction
Predicting faults in software aims to detect defects before the testing phase, allowing for
better resource allocation and high-quality software development, which is a requisite for …
better resource allocation and high-quality software development, which is a requisite for …
[HTML][HTML] Multimodel phishing url detection using lstm, bidirectional lstm, and gru models
In today's world, phishing attacks are gradually increasing, resulting in individuals losing
valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers …
valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers …
[HTML][HTML] Intelligent decision forest models for customer churn prediction
Customer churn is a critical issue impacting enterprises and organizations, particularly in the
emerging and highly competitive telecommunications industry. It is important to researchers …
emerging and highly competitive telecommunications industry. It is important to researchers …
[HTML][HTML] SMSPROTECT: An automatic smishing detection mobile application
Abstract Short Messaging Service (SMS) has grown to become the most widely used feature
in mobile devices. The technological advancements that birthed other alternative messaging …
in mobile devices. The technological advancements that birthed other alternative messaging …
[HTML][HTML] Empirical analysis of tree-based classification models for customer churn prediction
Customer churn is a vital and reoccurring problem facing most business industries,
particularly the telecommunications industry. Considering the fierce competition among …
particularly the telecommunications industry. Considering the fierce competition among …
[HTML][HTML] Empirical analysis of data streaming and batch learning models for network intrusion detection
Network intrusion, such as denial of service, probing attacks, and phishing, comprises some
of the complex threats that have put the online community at risk. The increase in the …
of the complex threats that have put the online community at risk. The increase in the …
Hybrid unsupervised web-attack detection and classification–A deep learning approach
S Pillai, A Sharma - Computer Standards & Interfaces, 2023 - Elsevier
Web requests made by users of web applications are manipulated by hackers to gain control
of web servers. Moreover, detecting web attacks has been increasingly important in the …
of web servers. Moreover, detecting web attacks has been increasingly important in the …
[HTML][HTML] An adaptive rank aggregation-based ensemble multi-filter feature selection method in software defect prediction
Feature selection is known to be an applicable solution to address the problem of high
dimensionality in software defect prediction (SDP). However, choosing an appropriate filter …
dimensionality in software defect prediction (SDP). However, choosing an appropriate filter …
[HTML][HTML] Software defect prediction using wrapper feature selection based on dynamic re-ranking strategy
Finding defects early in a software system is a crucial task, as it creates adequate time for
fixing such defects using available resources. Strategies such as symmetric testing have …
fixing such defects using available resources. Strategies such as symmetric testing have …
A systematic review: Detecting phishing websites using data mining models
D Jibat, S Jamjoom, QA Al-Haija… - Intelligent and …, 2023 - ieeexplore.ieee.org
As internet technology use is on the rise globally, phishing constitutes a considerable share
of the threats that may attack individuals and organizations, leading to significant losses from …
of the threats that may attack individuals and organizations, leading to significant losses from …