AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
An automated phishing detection system using Artificial Neural Networks to classify URLs as phishing or legitimate, outperforming Logistic Regression, SVM, SVM, and Random Forest baselines.
The development of internet technology has increased the intensity of digital activities, but it has also been followed by an increase in cybersecurity threats, one of which is phishing attacks through malicious URLs. Phishing is a fraudulent method that is carried out by manipulating users through fake websites that r...
A Phishing Website Detection System Using a Stacked Hybrid Model With Explainable AI, designed to accurately classify websites as phishing or legitimate while providing transparent decision explanations, is presented.
Phishing websites continue to be a major cybersecurity threat because attackers create deceptive web pages that imitate trusted banking, e-commerce, social media, and government platforms to collect sensitive user information. Traditional blacklist-based and rule-based detection methods are limited because they mainly...
An Explainable Ensemble Artificial Intelligence Framework for Real Time Phishing Website Detection that addresses the primary weakness of existing systems and is deployed as a real-time desktop application.
The internet has rapidly evolved in its communication, commerce and information sharing making it a huge platform for cyber threats, particularly malicious URLs. They pose a serious threat to individuals and to organisations. Phishing attacks, malware distribution and other types of cybercrime frequently are carried ou...
A hybrid real-time phishing detection system in the form of a Google Chrome extension that uses a trusted domain whitelist for false positives on legitimate banking and government websites and a pattern-based blocklist for piracy and malware domains.
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