Malicious advertisement URLs pose a security risk since they are the source of cyber-attacks, and need to address this issue is growing in both industry academia. Several attempts have been made recent years for malicious URL detection using machine learning (ML). The most widely used techniques extract linguistic features string like bag-of-words (BoW) before applying ML model. Existing requir...

Phishing is a social engineering cyberattack where criminals deceive users to obtain their credentials through login form that submits the data malicious server. In this paper, we compare machine learning and deep techniques present method capable of detecting phishing websites URL analysis. most current state-of-the-art solutions dealing with detection, legitimate class made up homepages witho...

Existence of spam URLs over emails and Online Social Media (OSM) has become a growing phenomenon. To counter the dissemination issues associated with long complex URLs in emails and character limit imposed on various OSM (like Twitter), the concept of URL shortening gained a lot of traction. URL shorteners take as input a long URL and give a short URL with the same landing page in return. With ...

ML-based Phishing URL (MLPU) detectors serve as the first level of defence to protect users and organisations from being victims phishing attacks. Lately, few studies have launched successful adversarial attacks against specific MLPU raising questions on their practical reliability usage. Nevertheless, robustness these systems has not been extensively investigated. Therefore, security vulnerabi...