Quo Vadis: Hybrid Machine Learning Meta-Model Based on Contextual and Behavioral Malware Representations-Reference-Cited by-同舟云学术

Quo Vadis: Hybrid Machine Learning Meta-Model Based on Contextual and Behavioral Malware Representations

Published:2022-11-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security
language:
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Author:

Trizna Dmitrijs¹

Affiliation:

1. Microsoft Corporation, Prague, Czech Rep

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3560830.3563726

Reference44 articles.

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2. Rakshit Agrawal Jack W. Stokes Mady Marinescu and Karthik Selvaraj. 2018. Robust Neural Malware Detection Models for Emulation Sequence Learning. arXiv:1806.10741 [cs.AI] Rakshit Agrawal Jack W. Stokes Mady Marinescu and Karthik Selvaraj. 2018. Robust Neural Malware Detection Models for Emulation Sequence Learning. arXiv:1806.10741 [cs.AI]

3. Hyrum S. Anderson Anant Kharkar Bobby Filar David Evans and Phil Roth. 2018. Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning. arXiv:1801.08917 [cs.CR] Hyrum S. Anderson Anant Kharkar Bobby Filar David Evans and Phil Roth. 2018. Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning. arXiv:1801.08917 [cs.CR]

4. Hyrum S. Anderson and Phil Roth . 2018 . EMBER : An Open Dataset for Training Static PE Malware Machine Learning Models . arXiv:1804.04637 [cs.CR] Hyrum S. Anderson and Phil Roth. 2018. EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models. arXiv:1804.04637 [cs.CR]

5. Malware classification with LSTM and GRU language models and a character-level CNN

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