TransMalDE: An Effective Transformer Based Hierarchical Framework for IoT Malware Detection-Reference-Cited by-同舟云学术

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TransMalDE: An Effective Transformer Based Hierarchical Framework for IoT Malware Detection

Published:2024-01 Issue:1 Volume:11 Page:140-151
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Deng Xiaoheng¹^ORCID,Wang Zhe²^ORCID,Pei Xinjun²^ORCID,Xue Kaiping³^ORCID

Affiliation:

1. School of Electronic Information, Central South University, Changsha, China

2. School of Computer Science and Engineering, Central South University, Changsha, China

3. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

National Natural Science Foundation of Hunan Province

Local Science and Technology Developing Fundation guided by Central Goverment

Key Project of Shenzhen City Special Fund for Fundamental Research

Opening Project of State Key Laboratory of Nickel and Cobalt Resources Comprehensive Utilization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6488902/10382160/10174662.pdf?arnumber=10174662

Reference39 articles.

1. Hybrid Malware Detection Based on Bi-LSTM and SPP-Net for Smart IoT

2. A Knowledge Transfer-based Semi-Supervised Federated Learning for IoT Malware Detection

3. FedCPF: An Efficient-Communication Federated Learning Approach for Vehicular Edge Computing in 6G Communication Networks

4. Edge-based IIoT Malware Detection for Mobile Devices with Offloading

5. Cloud Based Malware Detection Through Behavioral Entropy

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