• Jeevan N M
• Karan B
• Sowmiya J S
• Teja Babu M

The web extension project aims to address the issue of online security by providing users with a fast and automated way of detecting the safety of URLs. To achieve this, the project involves several steps such as tokenizing, stemming, and joining words from URLs. This is done to improve the accuracy of the algorithm and make it more effective in detecting potentially harmful websites. The model used in this project is based on logistic regression, which is a widely used machine learning algorithm in various applications, including text classification. By using this model, the resulting web extension can detect potentially dangerous URLs with high accuracy. The benefit of this approach is that users no longer need to manually check URLs, saving time and ensuring safe browsing. Overall, this project provides an innovative and practical solution for enhancing online security and ensuring a safer browsing experience for users.

Phishing detection, Secure website, Unsecure website, Logistic Regression Algorithm (LRA), Machine learning.

"Phishing Detection Extension Using Logistic Regression Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.h230-h235, May-2023, Available :http://www.jetir.org/papers/JETIR2305729.pdf

"Phishing Detection Extension Using Logistic Regression Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pph230-h235, May-2023, Available at : http://www.jetir.org/papers/JETIR2305729.pdf