Cyber Security Project (College Project 6 month training)
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Updated
Jun 13, 2024 - HTML
Cyber Security Project (College Project 6 month training)
Malicious URL Detection is designed to identify potentially harmful URLs using machine learning techniques. The model leverages various features of URLs to classify them as malicious or benign, providing an essential prediction for cybersecurity.
Using Random Forest to detect Malicious attacks on the ES6 Website
detect malicious urls in twitch chat and delete those messages using machine learning and NLP
Implement machine learning and deep learning algorithms for malicious URL detection
Machine Learning Based Ransomware generated Command and Control Domain Detector.
Malicious Url Detection
Python code for detecting malicious website from given dataset
Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.
Malicious URL Detection using Machine Learning
TrustLink: Detect and safeguard against deceptive URLs. Real-time threat detection using browser extension and web application for enhanced online security.
A Python 3 script that checks if a single URL, or multiple URLs, are malicious.
🔐 Identifies dark patterns online, Summarizes the privacy policy of a website, Malicious URL detection, Multilingual support & more ...
Experienced Analyst with a demonstrated history of working in insurance and IT industry. Machine Learning Enthusiast. Stay Tuned.
A New Framework for Characterizing Hosts on the Internet Based on Deep Learning
This project classifies and detects malicious websites by analyzing various factors such as the URL of the website, IP address, the geographic location of where the website is hosted and other factors.
A malicious URL detection system using Machine Learning. This was my dissertation for my BSc Computer Science degree at University of Southampton, which received a First-Class honours mark.
Detect whether a website is legitimate (or) phishing using machine learning techniques
free-nitro.club detection api; /links returns all links and /links/<link> checks if the link is malicious
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