Deep Learning Based Malapps Detection in Android Powered Mobile Cyber-Physical System
Author:
Affiliation:
1. University of Western Ontario,Department of Computer Science,London,ON,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10073968/10073976/10074208.pdf?arnumber=10074208
Reference24 articles.
1. MaxNet: Neural Network Architecture for Continuous Detection of Malicious Activity
2. Dynamic Android Malware Category Classification using Semi-Supervised Deep Learning
3. End-Edge Coordinated Inference for Real-Time BYOD Malware Detection using Deep Learning
4. Efficient android malware scanner using hybrid analysis;kumar;International Journal of Recent Technology and Engineering (TM),2019
Cited by 3 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. Comparison and Investigation of AI-Based Approaches for Cyberattack Detection in Cyber-Physical Systems;IEEE Access;2024
2. A Comparative Performance Analysis of Android Malware Classification Using Supervised and Semi-supervised Deep Learning;2023 16th International Conference on Security of Information and Networks (SIN);2023-11-20
3. Android malware analysis and detection: A systematic review;Expert Systems;2023-10-25
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