Detection of Phishing and Suspicious URL Using Machine Learning
Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.9, No. 4)Publication Date: 2020-04-30
Authors : Narayana K E; Srinath R; Srivaths G; Varun S;
Page : 71-75
Keywords : Phishing website detection; Random Forest Regressor; Train test Split; Machine Learning; Cross Validation;
Abstract
Phishing is a fraudulent process or an attempt to steal one's personal information. Phishing usually occurs via email or by portraying website as a legitimate one. In order to stop the phishing attempt we have to find or recognize the phish. The solution to the problem requires Random Forest (RF), one of the different types of machine learning based algorithms used for detection of Phishing websites. Finally we measured and compared the performance of the regressor in terms of accuracy and with the help of values generated from given conditions are predicted.We provided an accuracy of 79% and combination of 17 features.
Other Latest Articles
- Impact of Thermal, Agitation and Microwave Assisted Extraction Techniques on Ascorbic Acid Content of Red Beet (Beta vulgaris L)
- Security and Usability Issues in Captcha Design
- Methods for Detection and Identification of Plasmodium Knowlesi: A Review Article
- A Proposal for A Reverse Logistics Model in The Automotive Sector in Mexico
- The Security of The Goods Through the Global Positioning System (GPS): Description and Application
Last modified: 2020-05-03 18:36:28