Optimizing AI for Mobile Malware Detection by Self-Built-Dataset GAN Oversampling and LGBM-Reference-Cited by-同舟云学术

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Optimizing AI for Mobile Malware Detection by Self-Built-Dataset GAN Oversampling and LGBM

Published:2023-07-31 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Cyber Security and Resilience (CSR)
language:
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Author:

Dayan Ortal¹,Wolf Lior¹,Wang Fang²,Harel Yaniv³

Affiliation:

1. School of Computer Science Tel-Aviv University,Tel-Aviv,Israel

2. C2PS, Khalifa University,Department of Electrical Engineering and Computer Science,Abu Dhabi,United Arab Emirates

3. Blavatnik Interdisciplinary Research Center Tel-Aviv University,Tel-Aviv,Israel

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10224900/10224823/10224927.pdf?arnumber=10224927

Reference33 articles.

1. Cyber Security and the Role of Intelligent Systems in Addressing its Challenges

2. Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review

3. A Systematic Review on Machine Learning and Deep Learning Models for Electronic Information Security in Mobile Networks

4. Artificial Intelligence Algorithms for Malware Detection in Android-Operated Mobile Devices

5. Identifying Applications' State via System Calls Activity;maasmi;2021 28th IEEE International Conference on Electronics Circuits and Systems (ICECS),2021

Cited by 1 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. Augmenting the diversity of imbalanced datasets via multi-vector stochastic exploration oversampling;Neurocomputing;2024-05

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