Abstract:
With the rise of internet-based scams and cyberattacks, phishing remains one of the most prevalent threats to online users. In response to this ongoing challenge, this re...Show MoreMetadata
Abstract:
With the rise of internet-based scams and cyberattacks, phishing remains one of the most prevalent threats to online users. In response to this ongoing challenge, this research paper presents the design and implementation of a Web Extension to enhance user security by identifying and alerting users to potential phishing websites in real time. Web Extension utilizes a combination of phishing detection techniques, including URL analysis, SSL certificate verification, and machine learning algorithms. By intelligently analyzing website URLs, the extension can detect suspicious patterns, misspellings, or anomalous subdomains commonly associated with phishing attempts. It further verifies the authenticity of SSL certificates to ensure a secure connection between users and websites. To enhance its accuracy, Web Extension can also leverage external APIs or databases containing known phishing websites. This cross referencing enables prompt identification of blacklisted websites and prevents users from inadvertently falling victim to phishing scams.
Date of Conference: 01-02 November 2023
Date Added to IEEE Xplore: 03 January 2024
ISBN Information: