XAI-AMD-DL: An Explainable AI Approach for Android Malware Detection System Using Deep Learning-Reference-Cited by-同舟云学术

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XAI-AMD-DL: An Explainable AI Approach for Android Malware Detection System Using Deep Learning

Published:2023-07-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE World Conference on Applied Intelligence and Computing (AIC)
language:
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Author:

Smmarwar Santosh K.¹,Gupta Govind P.¹,Kumar Sanjay¹

Affiliation:

1. National Institute of Technology,Department of Information Technology,Raipur,India,492010

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10263804/10263805/10263974.pdf?arnumber=10263974

Reference33 articles.

1. Machine learning aided Android malware classification

2. JOWMDroid: Android malware detection based on feature weighting with joint optimization of weight-mapping and classifier parameters

3. Discrete Wavelet Transform-based feature engineering for stock market prediction

4. A Hybrid Feature Selection Approach-Based Android Malware Detection Framework Using Machine Learning Techniques

5. DroidMalwareDetector: A novel Android malware detection framework based on convolutional neural network

Cited by 2 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. The revolution and vision of explainable AI for Android malware detection and protection;Internet of Things;2024-10

2. Securing Cloud-Encrypted Data: Detecting Ransomware-as-a-Service (RaaS) Attacks through Deep Learning Ensemble;Computers, Materials & Continua;2024

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