The power of obfuscation techniques in malicious JavaScript code: A measurement study
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx5/6449416/6460999/06461002.pdf?arnumber=6461002
Cited by 58 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. Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors;Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security;2023-11-26
2. Sustainability of Web Application Security Using Obfuscation: Techniques and Effects;Studies in Systems, Decision and Control;2023-10-04
3. Short- versus long-term performance of detection models for obfuscated MSOffice-embedded malware;International Journal of Information Security;2023-08-14
4. An Empirical Study on the Effects of Obfuscation on Static Machine Learning-Based Malicious JavaScript Detectors;Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis;2023-07-12
5. Obfuscated JavaScript Code Detection using Machine Learning with AST-based Syntactic and Lexical Analysis;2023 8th International Conference on Smart and Sustainable Technologies (SpliTech);2023-06-20
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