LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers

In this study, a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most critical building blocks in the security of the Android operating system, are extracted through stati...

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Main Authors: Durmus Ozkan Sahin, Sedat Akleylek, Erdal Kilic
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9694615/
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author Durmus Ozkan Sahin
Sedat Akleylek
Erdal Kilic
author_facet Durmus Ozkan Sahin
Sedat Akleylek
Erdal Kilic
author_sort Durmus Ozkan Sahin
collection DOAJ
description In this study, a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most critical building blocks in the security of the Android operating system, are extracted through static analysis, and security analyzes of applications are carried out with machine learning techniques. Based on the multiple linear regression techniques, two classifiers are proposed for permission-based Android malware detection. These classifiers are compared on four different datasets with basic machine learning techniques such as support vector machine, k-nearest neighbor, Naive Bayes, and decision trees. In addition, using the bagging method, which is one of the ensemble learning, different classifiers are created, and the classification performance is increased. As a result, remarkable performances are obtained with classification algorithms based on linear regression models without the need for very complex classification algorithms.
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publishDate 2022-01-01
publisher IEEE
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series IEEE Access
spelling doaj-art-c61d96c96b8947c2872fd65e70c1b1d92025-02-08T00:00:11ZengIEEEIEEE Access2169-35362022-01-0110142461425910.1109/ACCESS.2022.31463639694615LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based ClassifiersDurmus Ozkan Sahin0https://orcid.org/0000-0002-0831-7825Sedat Akleylek1https://orcid.org/0000-0001-7005-6489Erdal Kilic2https://orcid.org/0000-0003-1585-0991Department of Computer Engineering, Ondokuz Mayıs University, Samsun, TurkeyDepartment of Computer Engineering, Ondokuz Mayıs University, Samsun, TurkeyDepartment of Computer Engineering, Ondokuz Mayıs University, Samsun, TurkeyIn this study, a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most critical building blocks in the security of the Android operating system, are extracted through static analysis, and security analyzes of applications are carried out with machine learning techniques. Based on the multiple linear regression techniques, two classifiers are proposed for permission-based Android malware detection. These classifiers are compared on four different datasets with basic machine learning techniques such as support vector machine, k-nearest neighbor, Naive Bayes, and decision trees. In addition, using the bagging method, which is one of the ensemble learning, different classifiers are created, and the classification performance is increased. As a result, remarkable performances are obtained with classification algorithms based on linear regression models without the need for very complex classification algorithms.https://ieeexplore.ieee.org/document/9694615/Ensemble learninglinear regressionmachine learningmalware analysispermission-based android malware detectionstatic analysis
spellingShingle Durmus Ozkan Sahin
Sedat Akleylek
Erdal Kilic
LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
IEEE Access
Ensemble learning
linear regression
machine learning
malware analysis
permission-based android malware detection
static analysis
title LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
title_full LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
title_fullStr LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
title_full_unstemmed LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
title_short LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
title_sort linregdroid detection of android malware using multiple linear regression models based classifiers
topic Ensemble learning
linear regression
machine learning
malware analysis
permission-based android malware detection
static analysis
url https://ieeexplore.ieee.org/document/9694615/
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AT sedatakleylek linregdroiddetectionofandroidmalwareusingmultiplelinearregressionmodelsbasedclassifiers
AT erdalkilic linregdroiddetectionofandroidmalwareusingmultiplelinearregressionmodelsbasedclassifiers