Self-Supervised Vision Transformers for Malware Detection-Reference-Cited by-同舟云学术

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Self-Supervised Vision Transformers for Malware Detection

Published:2022 Issue: Volume:10 Page:103121-103135
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Seneviratne Sachith¹^ORCID,Shariffdeen Ridwan²,Rasnayaka Sanka²^ORCID,Kasthuriarachchi Nuran³

Affiliation:

1. Faculty of Engineering and IT, University of Melbourne, Parkville, VIC, Australia

2. School of Computing, National University of Singapore, Queenstown, Singapore

3. Department of Computer Science and Engineering, University of Moratuwa, Moratuwa, Sri Lanka

Funder

Australian NHMRC

LIEF HPC-GPGPU Facility hosted at the University of Melbourne

LIEF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09889730.pdf?arnumber=9889730

Reference67 articles.

1. Deep neural network based malware detection using two dimensional binary program features

2. Improving malware classification

3. Malware classification and composition analysis: A survey of recent developments

4. ImageNet: A large-scale hierarchical image database

5. Spartan performance and flexibility: An HPC-cloud chimera;lev lafayette;Proc OpenStack Summit,2016

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1. TDBAMLA: Temporal and dynamic behavior analysis in Android malware using LSTM and attention mechanisms;Computer Standards & Interfaces;2025-03

2. VINCENT: Cyber-threat detection through vision transformers and knowledge distillation;Computers & Security;2024-09

3. A review of deep learning based malware detection techniques;Neurocomputing;2024-09

4. MalSort: Lightweight and efficient image-based malware classification using masked self-supervised framework with Swin Transformer;Journal of Information Security and Applications;2024-06

5. MalViT: An Approach to Enhancing Malware Detection;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09

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