Comparing Classifiers: A Look at Machine-Learning and the Detection of Mobile Malware in COVID-19 Android Mobile Applications-Reference-Cited by-同舟云学术

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Comparing Classifiers: A Look at Machine-Learning and the Detection of Mobile Malware in COVID-19 Android Mobile Applications

Published:2023-10-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing
language:
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Author:

Johnson Seth¹^ORCID,Donner Ray¹^ORCID,Perez Alfredo J.²^ORCID

Affiliation:

1. University of Nebraska at Omaha, Omaha, Nebraska, USA

2. University of Nebraska at Omaha, Omaha, Nebraska, United States of America

Funder

National Science Foundation

Publisher

ACM

Reference9 articles.

1. A Novel Approach to Detect Android Malware

2. Applying machine learning classifiers to dynamic Android malware detection at scale

3. SMOTE: Synthetic Minority Over-sampling Technique

4. Cybercrimes during COVID -19 Pandemic

5. Beyond the virus: a first look at coronavirus-themed Android malware

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