Using Lexical Features for Malicious URL Detection -- A Machine Learning Approach

Understand

Malicious websites are responsible for a majority of the cyber-attacks and scams today.

• Malicious URLs are delivered to unsuspecting users via email, text messages, pop-ups or advertisements.
• Clicking on or crawling such URLs can result in compromised email accounts, launching of phishing campaigns, download of malware, spyware and ransomware, as well as severe monetary losses.
• A machine learning based ensemble classification approach is proposed to detect malicious URLs in emails, which can be extended to other methods of delivery of malicious URLs.