Efficient Classification of Malicious URLs: M-BERT—A Modified BERT Variant for Enhanced Semantic Understanding-Reference-Cited by-同舟云学术

Efficient Classification of Malicious URLs: M-BERT—A Modified BERT Variant for Enhanced Semantic Understanding

Published:2024 Issue: Volume:12 Page:13453-13468
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Yu Boyang¹^ORCID,Tang Fei¹,Ergu Daji¹,Zeng Rui²,Ma Bo¹,Liu Fangyao¹^ORCID

Affiliation:

1. College of Electronics and Information, Southwest Minzu University, Chengdu, China

2. College of Pharmacy, Southwest Minzu University, Chengdu, China

Funder

Southwest Minzu University Research Startup Funds

National Natural Science Foundation of China

Science and Technology Planning Project of Sichuan Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10411887.pdf?arnumber=10411887

Reference37 articles.

1. Malicious URL detection using machine learning: A survey;Sahoo;arXiv:1701.07179,2017

2. Malicious URL detection with feature extraction based on machine learning

3. Towards detecting and classifying malicious URLs using deep learning;Johnson;J. Wireless Mobile Netw. Ubiquitous Comput. Dependable Appl.,2020

4. EXpose: A character-level convolutional neural network with embeddings for detecting malicious URLs, file paths and registry keys;Saxe;arXiv:1702.08568,2017

5. The PageRank citation ranking: Bringing order to the web;Brin

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