An Efficient Approach to Detect Fraudulent Service Enrollment Websites with Novel Random Forest and Compare the Accuracy with XGBoost Machine Algorithm

S Meghana - E3S Web of Conferences, 2023 - e3s-conferences.org
Aim: The main aim of this research study is to detect fraudulent service enrollment websites
using the Novel Random Forest algorithm and compare its accuracy with the XGBoost …

Fraudulent e-commerce website detection model using html, text and image features

MN Kassim, MA Maarof… - Proceedings of the 11th …, 2020 - books.google.com
Many of Internet users have been the victims offraudulent e-commerce websites and the
number grows. This paper presents an investigation on three types of features namely HTML …

Fake Website Prediction Using Random Forest

C Mythilipriya, S Priyadharshini, S Karan… - … on Electronics and …, 2021 - ieeexplore.ieee.org
Fake websites are now producing billions of dollars in fraud at the cost of innocent Internet
users. Users will have a difficult time manually identifying these websites as phoney due to …

Fraudulent e-commerce website detection model using HTML, text and image features

E Khoo, A Zainal, N Ariffin, MN Kassim… - Proceedings of the 11th …, 2021 - Springer
Many of Internet users have been the victims of fraudulent e-commerce websites and the
number grows. This paper presents an investigation on three types of features namely HTML …

Comparison of Novel Optimized Random Forest Technique and Support Vector Machine for Fraudulent activities in credit card Detection with Improved Precision

MSSA Baig, K Jaisharma - 2023 Eighth International …, 2023 - ieeexplore.ieee.org
The objective in the research work is to determine fraudulent activities in credit card using
Novel Optimized Random Forest Technique (NORFT) algorithm with comparison of Support …

Content based fraudulent website detection using supervised machine learning techniques

M Maktabar, A Zainal, MA Maarof… - Hybrid Intelligent Systems …, 2018 - Springer
Fraudulent websites pose as legitimate sources of information, goods, product and services
are propagating and resulted in loss of billions of dollars. Due to several undesirable …

Using attribute-based feature selection approaches and machine learning algorithms for detecting fraudulent website URLs

M Aydin, I Butun, K Bicakci… - 2020 10th Annual …, 2020 - ieeexplore.ieee.org
Phishing is a malicious form of online theft and needs to be prevented in order to increase
the overall trust of the public on the Internet. In this study, for that purpose, the authors …

Detection of data breaching websites using machine learning

MR Prathap, KM Nandhini, KS Vairavel… - … on Advancements in …, 2021 - ieeexplore.ieee.org
In pandemic situation, the world has upgraded to virtual mode. From classes to work
everything turned to be online mode. So, the usage of internet and online services are rising …

Phishing website analysis and detection using Machine Learning

A Chawla - International Journal of Intelligent Systems and …, 2022 - ijisae.org
Cybersecurity has become an essential part of this new digital age with more than 820
million users of internet by the year 2022 there is need of security systems to protect public …

A smart methodology for analyzing secure e-banking and e-commerce websites

RMA Latif, M Umer, T Tariq, M Farhan… - … on Applied Sciences …, 2019 - ieeexplore.ieee.org
Acquiring sensitive information from the user in some malicious web pages which looks like
the legitimate webpage and they do a kind of criminal activity that is known as phishing in …