Results 131 to 140 of about 4,265,497 (230)

Risky business: managing electronic payments in the 21st Century [PDF]

On June 20 and 21, 2005, the Payment Cards Center of the Federal Reserve Bank of Philadelphia, in conjunction with the Electronic Funds Transfer Association (EFTA), hosted a day-and-a-half forum, “Risky Business: Managing Electronic Payments in the 21st ...
Marilyn Bochicchio, Stanley Sienkiewicz
core  

Phishing to improve detection

Proceedings of the 2023 European Symposium on Usable Security, 2023
Sarah Ying Zheng, Ingolf Becker
openaire   +1 more source

PHISHSIM: Phishing Website Detection

International Research Journal on Advanced Engineering and Management (IRJAEM)
In this paper, we introduce a powerful new approach for detecting phishing websites that is entirely feature-free. Our method, called PhishSim, uses the Normalized Compression Distance (NCD), a technique that requires no specialized parameters. NCD works by measuring the similarity of two websites through compression, eliminating the time and effort ...
null Nivyashree R, null Bhoomika S R, null Chiranth H M, null Bhavan N Gowda, null Chakram Janya H U   +4 more
openaire   +1 more source

Catch Me If You See: Using Visual Cue and Explanatory Feedback to Enhance Human Phishing Detection

IEEE Access
Phishing attacks are a major cybersecurity threat that exploit human weaknesses to steal sensitive information. Although detection systems have improved, phishing attacks remain widespread which highlights the need for human-centered defenses.
Arifa I. Champa, Md Fazle Rabbi, Farjana Z. Eishita, Minhaz F. Zibran   +3 more
doaj   +1 more source

Explainable Machine Learning for Phishing Site Detection: A High‐Efficiency Approach Using Boosting Models and SHAP

The Journal of Engineering
Nowadays, a wide range of electronic devices are being connected through the internet, and a wide range of cybercrimes are being coordinated. Phishing is one of the most serious online crimes.
Khandaker Mohammad Mohi Uddin, Nitish Biswas, Sarreha Tasmin Rikta, Md. Nur ‐A‐Alam, Rafid Mostafiz   +4 more
doaj   +1 more source

Towards Adversarial Phishing Detection

, 2020
Over the recent decades, numerous evaluations of automated methods for detecting phishing attacks have been reporting stellar detection performances based on empirical evidence. These performances often neglect the adaptive behavior of an adversary seeking to evade detection, yielding uncertainty about their adversarial robustness.
Panum, Thomas K., Hageman, Kaspar, Hansen, Rene Rydhof; id_orcid 0000-0002-5688-6432, Pedersen, Jens Myrup; id_orcid 0000-0002-1903-2921   +3 more
openaire   +1 more source

Hybrid MLOps framework for automated lifecycle management of adaptive phishing detection models. [PDF]

Sci Rep
Reda A, Taie SA, Shaheen ME.
europepmc   +1 more source

Phishing detection on webpages in European non-English languages based on machine learning. [PDF]

Sci Rep
Komosny D.
europepmc   +1 more source

Phish-Hook: Phishing Site Detection using URL Features

International Journal for Research in Applied Science and Engineering Technology, 2020
openaire   +1 more source

A hybrid super learner ensemble for phishing detection on mobile devices. [PDF]

Sci Rep
Rao RS, Kondaiah C, Pais AR, Lee B.
europepmc   +1 more source