Cloud of Word vs DroidKungfu: Performance Evaluation in Detecting Root Exploit Malware with Deep Learning Approach-Reference-Cited by-同舟云学术

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Cloud of Word vs DroidKungfu: Performance Evaluation in Detecting Root Exploit Malware with Deep Learning Approach

Published:2023-08-25 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS)
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Author:

Yahaya Che Akmal Che¹,Firdaus Ahmad²,Zabidi Azlee²,Bt Abu Bakar Noor Akma³,Bt Nawir Mukrimah¹,Malek Philimal Normelissa Ani Abdul¹

Affiliation:

1. Tunku Abdul Rahman University of Management and Technology,Faculty of Computing and Information Technology,Kuantan,Pahang,Malaysia

2. Universiti Malaysia Pahang Al-Sultan Abdullah,Faculty of Computing,Pekan,Pahang,Malaysia

3. Universiti Malaysia Pahang Al-Sultan Abdullah,Faculty of Industry and Management,Gambang,Pahang,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10256260/10256269/10256304.pdf?arnumber=10256304

Reference28 articles.

1. Android Malware Datasets;ArgusLab,0

2. Recurrent neural network for malware detection;halim;International Journal of Advances in Soft Computing and Its Applications,2019

3. Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network

4. SeqDroid: Obfuscated Android Malware Detection Using Stacked Convolutional and Recurrent Neural Networks

5. Opcode sequence analysis of Android malware by a convolutional neural network

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