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Detection of Malicious Android Applications: Classical Machine Learning
  vs. Deep Neural Network Integrated with Clustering

Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering

International Conference on Broadband Communications, Networks and Systems (BROADNETS), 2021
28 February 2021
Hemant Rathore
S. K. Sahay
Shivin Thukral
Mohit Sewak
ArXiv (abs)PDFHTML

Papers citing "Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering"

5 / 5 papers shown
Feature-Centric Approaches to Android Malware Analysis: A Survey
Feature-Centric Approaches to Android Malware Analysis: A Survey
Shama Maganur
Yili Jiang
Jiaqi Huang
Fangtian Zhong
144
3
0
12 Sep 2025
Deep Reinforcement Learning for Cybersecurity Threat Detection and
  Protection: A Review
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A ReviewSecure Knowledge Management (SKM), 2022
Mohit Sewak
S. K. Sahay
Hemant Rathore
AAML
210
38
0
06 Jun 2022
LSTM Hyper-Parameter Selection for Malware Detection: Interaction
  Effects and Hierarchical Selection Approach
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection ApproachIEEE International Joint Conference on Neural Network (IJCNN), 2021
Mohit Sewak
S. K. Sahay
Hemant Rathore
177
5
0
23 Sep 2021
ADVERSARIALuscator: An Adversarial-DRL Based Obfuscator and Metamorphic
  Malware SwarmGenerator
ADVERSARIALuscator: An Adversarial-DRL Based Obfuscator and Metamorphic Malware SwarmGeneratorIEEE International Joint Conference on Neural Network (IJCNN), 2021
Mohit Sewak
S. K. Sahay
Hemant Rathore
AAML
177
10
0
23 Sep 2021
DRo: A data-scarce mechanism to revolutionize the performance of Deep
  Learning based Security Systems
DRo: A data-scarce mechanism to revolutionize the performance of Deep Learning based Security Systems
Mohit Sewak
S. K. Sahay
Hemant Rathore
225
5
0
12 Sep 2021
1
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