Phishing attacks trick victims into disclosing sensitive information. To counter them, we
explore machine learning and deep learning models leveraging large-scale data. We …

Recent years have seen the development of phishing detection and identification
approaches to defend against phishing attacks. Phishing detection solutions often report …

Phishing attacks are a critical and escalating cybersecurity threat in the modern digital
landscape. As cybercriminals continually adapt their techniques, automated phishing …

As the use of machine learning (ML) models is becoming increasingly popular in many real-
world applications, there are practical challenges that need to be addressed for model …

Existing literature on adversarial Machine Learning (ML) focuses either on showing attacks
that break every ML model, or defenses that withstand most attacks. Unfortunately, little …

Phishing continues to be a major security concern for organizations around the globe. Past
works proposed classifiers to detect phishing emails; however many of them are based on …

Recent times have witnessed the rise of anti-phishing schemes powered by deep learning
(DL). In particular, logo-based phishing detectors rely on DL models from Computer Vision …

Abstract The Internet of things (IoT) has been emerging technology for the past decade. IoT
can be defined as the network connecting objects to the Internet in the physical world. IoT …

In recent years, phishing websites have constantly evolved, causing traditional URL or
HTML-based detection methods less effective. This limitation motivated the development of …

ÐBlack-box web vulnerability scanners are invaluable for security researchers and
practitioners. Despite recent approaches tackling some of the inherent limitations of …