Results 101 to 110 of about 3,253,884 (197)

A Sophisticated Framework for the Accurate Detection of Phishing Websites

CoRR
Phishing is an increasingly sophisticated form of cyberattack that is inflicting huge financial damage to corporations throughout the globe while also jeopardizing individuals' privacy. Attackers are constantly devising new methods of launching such assaults and detecting them has become a daunting task.
Asif Newaz, Farhan Shahriyar Haq, Nadim Ahmed   +2 more
openaire   +2 more sources

Software module for detecting fraudulent websites using classification based on machine learning methods

Informatika
O b j e c t i v e s. Phishing web resources are among the most common tools of online fraud aimed at obtaining users' confidential information. The goal of this research was to develop a software module for the automatic detection of phishing websites ...
S. N. Petrov, A. O. Myadelets, E. V. Kundas   +2 more
doaj   +1 more source

Machine Learning for Phishing Website Detection [PDF]

Phishing attacks are on the rise and phishing websites are everywhere, denoting the brittleness of security mechanisms reliant on blocklists. Prior work proposed en- hancing Phishing Website Detectors (PWD) to mitigate this threat with data-driven ...
YUAN, YING
core  

Feature Engineering for Phishing Website Detection Using Machine Learning: A Systematic Review

IEEE Access
Phishing website detection has been widely explored, yet most existing surveys focus on detection algorithms or general cybersecurity methods, offering only a brief treatment of feature engineering. This systematic literature review addresses this gap by
Yanche Ari Kustiawan, Khairil Imran Ghauth   +1 more
doaj   +1 more source

Tree-based Ensemble Machine Learning for Phishing Website Detection

Komputika
Phishing remains a prevalent and perilous cyber threat in the digital age, exploiting human vulnerabilities to deceive individuals into disclosing sensitive information. This paper presents a method to achieve high accuracy in phishing website detection
Husni Fadhilah, Diky Restu Maulana, Rahayu Utari   +2 more
doaj   +1 more source

To deceive or not to deceive! Legal implications of phishing covert research

, 2013
Whilst studying mobile users' susceptibility to phishing attacks, we found ourselves subject to regulations concerning the use of deception in research. We argue that such regulations are misapplied in a way that hinders the progress of security research.
Sugiura, Lisa
core   +1 more source

A Novel Architecture Based on Weight Freezing and Random Forest for Website Phishing Detection

International Journal of Computational Intelligence Systems
Phishing is a severe cybersecurity threat that continues to cause significant economic losses and breaches of privacy globally. This paper presents a novel architecture for effective phishing website detection, integrating a unique weight freezing ...
Ali Jasim Khaleefah AL-JABERI, Sefer Kurnaz, Raghda Awad Shaban Naseri, Hameed Mutlag Farhan   +3 more
doaj   +1 more source

Evasion Attacks and Defense Mechanisms for Machine Learning-Based Web Phishing Classifiers

IEEE Access
Phishing is an electronic fraud through which an attacker can access user credentials. Phishing websites are the ones that mimic legitimate websites. Fraudsters can replace them within hours to evade their detection.
Manu J. Pillai, S. Remya, V. Devika, Somula Ramasubbareddy, Yongyun Cho   +4 more
doaj   +1 more source

Phishing detection algorithm based on attention and feature fusion

网络与信息安全学报
Phishing has been the primary means utilized by attackers to conduct cyber fraud. As national anti-cyber fraud efforts continue to increase, the technical confrontation of various phishing activities has also escalated, bringing significant pressure to ...
Sirui ZHANG, Zhiwei YAN, Kejun DONG, Xuebiao YUCHI
doaj   +1 more source

Implementation of Phishing Detection and Defense Program using Ensemble Methods

This thesis implements a phishing detection and defense program using ensemble methods. Cybercrime is becoming increasingly sophisticated recently.
Miyashita, Yui
core