CNN based zero-day malware detection using small binary segments-Reference-Cited by-同舟云学术

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CNN based zero-day malware detection using small binary segments

Published:2021-10 Issue: Volume:38 Page:301128
ISSN:2666-2817
Container-title:Forensic Science International: Digital Investigation
language:en
Short-container-title:Forensic Science International: Digital Investigation

Author:

Wen Qiaokun,Chow K.P.

Publisher

Elsevier BV

Subject

Law,Medical Laboratory Technology,Computer Science Applications,Information Systems,Pathology and Forensic Medicine

Reference12 articles.

1. Towards light-weight deep learning based malware detection;Kan,2018

2. Very Deep Convolutional Networks Forlarge-Scale Image Recognition;Karen,2014

3. Effective and efficient malware detection at the end host;Kolbitsch,2009

4. Malware Detection by Eating a Whole EXE;Raff,2017

5. Learning the Pe Header, Malware Detection with Minimal Domain Knowledge;Raff,2017

Cited by 3 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. Deep Learning for Zero-day Malware Detection and Classification: A Survey;ACM Computing Surveys;2023-09-15

2. Improving ransomware detection based on portable executable header using xception convolutional neural network;Computers & Security;2023-07

3. BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning;Security and Communication Networks;2022-10-11

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