Super Learner for Malicious URL Detection-Reference-Cited by-同舟云学术

Super Learner for Malicious URL Detection

Published:2022-02-23 Issue: Volume: Page:
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Container-title:2022 2nd International Conference on Advanced Research in Computing (ICARC)
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Author:

Hevapathige Asela¹,Rathnayake Kavindu²

Affiliation:

1. University of Ruhuna,Department of Electrical and Information Enigneering,Galle,Sri Lanka

2. Sri Lanka Institute of Information Technology,Faculty of Computing,Malabe,Sri Lanka

Publisher

IEEE

Link

Reference22 articles.

1. Empirical Study on Malicious URL Detection Using Machine Learning;patgiri,2021

2. Detecting phishing attacks using a combined model of LSTM and CNN;ariyadasa;International journal of advanced and applied sciences,2020

4. Two phase classification model to detect malicious URLs;jayakanthan;International Journal of Applied Engineering Research,2017

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2. Proactive Phishing Website URL Scanner;International Journal of Innovative Science and Research Technology (IJISRT);2024-06-07

3. Malicious Transaction URL Detection Using Logistic Regression;Proceedings of International Conference on Network Security and Blockchain Technology;2023-11-29

4. Performance Evaluation of Machine Learning Algorithms for Website Defacement Attack Detection;2023 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES);2023-07-07

5. Using Machine Learning to Detect and Classify URLs: A Phishing Detection Approach;2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC);2023-07-06