Results 11 to 20 of about 2,777,664 (208)
PhiKitA: Phishing Kit Attacks Dataset for Phishing Websites Identification
IEEE Access, 2023 Recent studies have shown that phishers are using phishing kits to deploy phishing attacks faster, easier and more massive. Detecting phishing kits in deployed websites might help to detect phishing campaigns earlier.
Felipe Castano +3 more
doaj +1 more source
Learning to detect phishing emails [PDF]
Proceedings of the 16th international conference on World Wide Web, 2006 Each month, more attacks are launched with the aim of making web users believe that they are communicating with a trusted entity for the purpose of stealing account information, logon credentials, and identity information in general. This attack method, commonly known as "phishing," is most commonly initiated by sending out emails with links to spoofed
Ian Fette +2 more
openaire +1 more source
International Journal of Networked and Distributed Computing (IJNDC), 2020 This article presents the threshold-based incremental learning model for a case-base updating approach that can support adaptive detection and incremental learning of Case-based Reasoning (CBR)-based automatic adaptable phishing detection.
San Kyaw Zaw, Sangsuree Vasupongayya
doaj +1 more source
Predicting Phishing Websites using Neural Network trained with Back-Propagation [PDF]
, 2013 Phishing is increasing dramatically with the development of modern technologies and the global worldwide computer networks. This results in the loss of customer’s confidence in e-commerce and online banking, financial damages, and identity theft ...
McCluskey, T.L. +2 more
core +3 more sources
PDGAN: Phishing Detection With Generative Adversarial Networks
IEEE Access, 2022 Phishing is a harmful online attack that could lead to identity theft and financial damages. The demand for high-accuracy phishing detection tools has risen due to the increase of online electronic services and payment systems.
Saad Al-Ahmadi +2 more
doaj +1 more source
SPWalk: Similar Property Oriented Feature Learning for Phishing Detection
IEEE Access, 2020 Detecting phishing webpages is an essential task that protects legitimate websites and their users from various malicious activities. To classify the suspect webpage as phishing or legitimate, robust and effective features used for classification are in ...
Xiuwen Liu, Jianming Fu
doaj +1 more source
An Assessment of Features Related to Phishing Websites using an Automated Technique [PDF]
, 2012 Corporations that offer online trading can achieve a competitive edge by serving worldwide clients. Nevertheless, online trading faces many obstacles such as the unsecured money orders.
McCluskey, T.L. +2 more
core +3 more sources
Intelligent phishing detection system for e-banking using fuzzy data mining [PDF]
, 2010 Detecting and identifying any phishing websites in real-time, particularly for e-banking, is really a complex and dynamic problem involving many factors and criteria. Because of the subjective considerations and the ambiguities involved in the detection,
Hossain, Alamgir +5 more
core +1 more source
Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions
IEEE Access, 2022 Phishing has become an increasing concern and captured the attention of end-users as well as security experts. Existing phishing detection techniques still suffer from the deficiency in performance accuracy and inability to detect unknown attacks despite
Nguyet Quang Do +4 more
doaj +1 more source
Intelligent Rule based Phishing Websites Classification [PDF]
, 2014 Phishing is described as the art of emulating a website of a creditable firm intending to grab user’s private information such as usernames, passwords and social security number.
Mohammad, Rami M. +4 more
core +1 more source