Interpreting Machine and Deep Learning Models for PDF Malware Detection using XAI and SHAP Framework
Author:
Affiliation:
1. BRAC University,Computer Science and Engineering,Dhaka,Bangladesh
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10100964/10100966/10101116.pdf?arnumber=10101116
Reference14 articles.
1. Grad-CAM for Visualizing Diabetic Retinopathy
2. Invasive weed optimization with stacked long short term memory for PDF malware detection and classification
3. Intelligent optimal gated recurrent unit based malicious pdf detection and classification model;pandi;Proceedings of the IEEE,2022
4. Explainable Artificial Intelligence in CyberSecurity: A Survey
5. Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more;bhattacharya;Packt Publishing,2022
Cited by 2 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. Interpretability of deep neural networks: A review of methods, classification and hardware;Neurocomputing;2024-10
2. XAI-PDF: A Robust Framework for Malicious PDF Detection Leveraging SHAP-Based Feature Engineering;The International Arab Journal of Information Technology;2024-01-01
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