Malicious Address Identifier (MAI): A Browser Extension to Identify Malicious URLs
Om Jaiswal, Parag Asare, Jitesh Gadgilwar, Kunal Rahangdale, Pratik Adekar, Leela Bitla, Sampada Wazalwar
Abstract
Many websites have emerged since the internet was introduced. Every day, people visit a variety of websites, and they unknowingly click on malicious URLs because they simply neglect to check the URLs they visit. Clicking on a malicious URL has significant consequences. People might become victims of a phishing attack, which aims to steal people’s money or identities by tricking them into disclosing their personal data such as passwords, credit card numbers, and bank account numbers on websites that portray themselves as legitimate. They might also have malware automatically installed on their computer devices, which can harm and destroy their systems. Therefore, if people don’t know whether a URL is malicious or not, something more dangerous might happen. In this paper, we present a browser extension that employs a two-layer model to identify malicious URLs on the web using Bi-LSTM and CNN algorithms. This extension not only identifies malicious URLs but also prevents them from being visited. Furthermore, it blocks ads so that users do not click on malicious URLs through ads.