An Empirical Study on the Effects of Obfuscation on Static Machine Learning-Based Malicious JavaScript Detectors-Reference-Cited by-同舟云学术

An Empirical Study on the Effects of Obfuscation on Static Machine Learning-Based Malicious JavaScript Detectors

Published:2023-07-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
language:
Short-container-title:

Author:

Ren Kunlun¹,Qiang Weizhong¹,Wu Yueming²,Zhou Yi¹,Zou Deqing¹,Jin Hai¹

Affiliation:

1. Huazhong University of Science and Technology, China

2. Nanyang Technological University, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597926.3598146

Reference73 articles.

1. 2023. Atom: A Hackable Text Editor for the 21st Century . https://atom.io/ 2023. Atom: A Hackable Text Editor for the 21st Century. https://atom.io/

2. 2023. AV Comparative Analyses. https://blog.virustotal.com/ 2012 /08/avcomparative-analyses-marketing-and.html 2023. AV Comparative Analyses. https://blog.virustotal.com/ 2012 /08/avcomparative-analyses-marketing-and.html

3. 2023. Closure-compiler. https://github.com/google/closure-compiler 2023. Closure-compiler. https://github.com/google/closure-compiler

4. 2023. Closure Compiler: Advanced Compilation. https://developers.google.com/ closure/compiler/docs/api-tutorial3 2023. Closure Compiler: Advanced Compilation. https://developers.google.com/ closure/compiler/docs/api-tutorial3

5. 2023. CodeBERT. https://github.com/microsoft/CodeBERT 2023. CodeBERT. https://github.com/microsoft/CodeBERT

Cited by 1 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. Efficient IoT Malware Detection Using Convolution Neural Network and View-Invariant Block;2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE);2023-11-17