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WebSHArk 1.0: A Benchmark Collection for Malicious Web Shell Detection
Journal of Information Processing Systems. 2015;11(2):229-238.   Published online 2015 April 20    DOI: https://doi.org/10.3745/JIPS.03.0026

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A Solution for Automatically Malicious Web Shell and Web Application Vulnerability Detection
Computational Collective Intelligence. 2016;367-378   
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CNN-Webshell
Proceedings of the 2017 VI International Conference on Network, Communication and Computing. 2017;75-79   
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Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection
Proceedings of the ACM Web Conference 2023. 2023;3660-3669   
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Effective analysis, characterization, and detection of malicious web pages
Proceedings of the 22nd International Conference on World Wide Web. 2013;355-360   
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Web Content Based Features for Malicious Web Page Detection Using Machine Learning
2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA). 2022;189-193   
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Malicious Web Links Detection Based on Image Processing and Deep Learning Models
2024 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). 2024;445-449   
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A Survey on Current Malicious JavaScript Behavior of infected Web Content in Detection of Malicious Web pages
IOP Conference Series: Materials Science and Engineering. 2020;769(1):012074   
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Web-Based Android Malicious Software Detection and Classification System
Applied Sciences. 2018;8(9):1622   
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SmartDetect: A Smart Detection Scheme for Malicious Web Shell Codes via Ensemble Learning
Smart Computing and Communication. 2018;196-205   
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Malicious URL detection by dynamically mining patterns without pre-defined elements
World Wide Web. 2013;17(6):1375-1394   
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