Disparity Analysis Between the Assembly and Byte Malware Samples with Deep Autoencoders-Reference-Cited by-同舟云学术

Disparity Analysis Between the Assembly and Byte Malware Samples with Deep Autoencoders

Published:2022-12-16 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
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Author:

Abdullah Muhammed Amin¹,Yu Yongbin¹,Cai Jingye¹,Imrana Yakubu²,Tettey Nartey Obed¹,Addo Daniel¹,Sarpong Kwabena¹,Agbley Bless Lord Y.²,Appiah Benjamin³

Affiliation:

1. University of Electronic Science and Technology of China,School of Information and Software Engineering,China

2. University of Electronic Science and Technology of China,School of Computer Science and Engineering,China

3. Ho Technical University,Department of Computer Science,Ho,Ghana

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10016263/10016475/10016485.pdf?arnumber=10016485

Reference9 articles.

1. IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture

2. Hcl-Classifier: Cnn and Lstm Based Hybrid Malware Classifier for Internet of Things(Iot)

3. Disrupting adversarial transferability in deep neural networks

4. Using a Subtractive Center Behavioral Model to Detect Malware

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