Performance Comparison of Recurrent Neural Networks for Metamorphic Malware
Author:
Affiliation:
1. School of Computer Science and Engineering, Vellore Institute of Technology,Vellore,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10244768/10244782/10245978.pdf?arnumber=10245978
Reference21 articles.
1. DL-FHMC: Deep Learning-based Fine-grained Hierarchical Learning Approach for Robust Malware Classification
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3. A Method for Automatic Android Malware Detection Based on Static Analysis and Deep Learning
4. Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm
5. Deep Learning and Visualization for Identifying Malware Families
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1. Optimizing hybrid neural networks for precise COVID-19 mRNA vaccine degradation prediction;International Journal of ADVANCED AND APPLIED SCIENCES;2024-07
2. A Robust Feature Integration for Multiclass Metamorphic Malware Detection in IoT Network;2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS);2024-01-03
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