Malware Family Classification via Residual Prefetch Artifacts

Author:

Duby Adam,Taylor Teryl,Zhuang Yanyan

Publisher

IEEE

Reference24 articles.

1. Neurlux

2. Leveraging virtual machine introspection with memory forensics to detect and characterize unknown malware using machine learning techniques at hypervisor;kumara;Digital Investigation,2017

3. Finding a needle in a haystack: The traffic analysis version;makhlouf;Proceedings on Privacy Enhancing Technologies,2019

4. A Behavior-Based Approach for Malware Detection

5. Malware classification with recurrent networks

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. Evaluating Feature Robustness for Windows Malware Family Classification;2022 International Conference on Computer Communications and Networks (ICCCN);2022-07

2. Detecting and Classifying Self-Deleting Windows Malware Using Prefetch Files;2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC);2022-01-26

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