SeqMobile: An Efficient Sequence-Based Malware Detection System Using RNN on Mobile Devices-Reference-Cited by-同舟云学术

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SeqMobile: An Efficient Sequence-Based Malware Detection System Using RNN on Mobile Devices

Published:2020-10 Issue: Volume: Page:
ISSN:
Container-title:2020 25th International Conference on Engineering of Complex Computer Systems (ICECCS)
language:
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Author:

Feng Ruitao,Lim Jing Qiang,Chen Sen,Lin Shang-Wei,Liu Yang

Funder

Singapore Ministry of Education

National Research Foundation

Singapore National Research Foundation

NCR

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9375908/9376180/09376205.pdf?arnumber=9376205

Cited by 11 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. A Dynamic Analysis Data Preprocessing Technique for Malicious Code Detection with TF-IDF and Sliding Windows;Electronics;2024-03-02

2. A Survey of Recent Advances in Deep Learning Models for Detecting Malware in Desktop and Mobile Platforms;ACM Computing Surveys;2024-01-22

3. SeqAdver: Automatic Payload Construction and Injection in Sequence-based Android Adversarial Attack;2023 IEEE International Conference on Data Mining Workshops (ICDMW);2023-12-04

4. Automatic Detection and Analysis towards Malicious Behavior in IoT Malware;2023 IEEE International Conference on Data Mining Workshops (ICDMW);2023-12-04

5. A Survey of Android Malware Detection Based on Deep Learning;Machine Learning for Cyber Security;2023

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