Analysing the Accuracy of Detecting Phishing Websites using Ensemble Methods in Machine Learning

Author:

Menaka S1,Harshika Jonnalagadda1,Philip Sarah1,John Rashi1,Bharathiraja N2,Murugesan S3

Affiliation:

1. SRM Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,India

2. Chitkara University Institute of Engineering and Technology,Department of Computer Science and Engineering,Chitkara University, Punjab, India.

3. Tagore Engineering College,Department of Information Technology,Rathinamangalam, Chennai,India

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Investigation of AI-Based Ensemble Methods for the Detection of Phishing Attacks;Engineering, Technology & Applied Science Research;2024-06-01

2. An Accuracy of Identifying Recyclable Objects and the Number of Objects Identified from Municipal Waste Without Occlusion Using Computer Vision Techniques;Innovations in Sustainable Technologies and Computing;2024

3. Classification and Identification of Phishing Websites based on Machine Learning;2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC);2023-11-02

4. Efficient Differentiation of Biodegradable and Non-Biodegradable Municipal Waste Using a Novel MobileYOLO Algorithm;Traitement du Signal;2023-10-30

5. To Improving the Performance of Identification and Segregation of Liquid and Solid from Municipal Waste Using Adam Optimization Algorithm;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18

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