Hybrid Optimization Based Long Short-Term Memory for Android Malware Detection-Reference-Cited by-同舟云学术

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Hybrid Optimization Based Long Short-Term Memory for Android Malware Detection

Published:2023-10-20 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
language:
Short-container-title:

Author:

Lande Jayapal¹,Maheswari M.²,Kamali S. M.³,Dineshkumar R.⁴,S Priyanka M⁵

Affiliation:

1. SR University,School of Computer Science & Artificial Intelligence,Warangal,India

2. SRM Institue of Science and Technology,School of Computing,Department of Computational Intelligence,Chennai,India

3. Annapoorana Engineering College,Department of Electrical and Electronics Engineering,Salem,India

4. Saveetha School of Engineering,Department of ECE,Sriperumbudur, Thandalam,India

5. Nitte Meenakshi Institute of Technology,Department of AI and ML,Yelahanka, Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10393408.pdf?arnumber=10393408

Reference14 articles.

1. A Bayesian probability model for Android malware detection

2. Mac OS X Malware Detection with Supervised Machine Learning Algorithms

3. BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning

4. M-FFN: multi-scale feature fusion network for image captioning

5. MH-DLdroid: A Meta-Heuristic and Deep Learning-Based Hybrid Approach for Android Malware Detection

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