Abstract :

PhishCatcher Is An Advanced Clientside Cybersecurity Solution Designed To Detect And Prevent Phishing And Web Spoofing Attacks Using Machine Learning Techniques. Phishing Attacks Often Trick Users Into Revealing Sensitive Information By Mimicking Legitimate Websites, And Traditional Detection Methods Struggle To Identify New And Evolving Threats.The Proposed System Introduces A Lightweight Browser Extension That Performs Realtime Analysis Of Web Pages By Extracting Features Such As URL Patterns, HTML Structure, And Domain Information. It Uses Machine Learning Algorithms Like Random Forest, Support Vector Machine (SVM), Gradient Boosting, And Neural Networks To Accurately Classify Websites And Reduce False Positives. PhishCatcher Operates Seamlessly In The Background, Providing Instant Alerts For Suspicious Websites While Maintaining User Browsing Performance. It Also Incorporates Adaptive Learning Through User Feedback And Updated Threat Intelligence To Improve Detection Over Time. Overall, The System Enhances Clientside Security By Providing A Scalable, Efficient, And User-friendly Solution For Safe And Secure Web Browsing.

Published:

15-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

2289 - 2297

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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