Is Malware Detection Needed for Android TV?

The smart TV ecosystem is rapidly expanding, allowing developers to publish their applications on TV markets to provide a wide array of services to TV users. However, this open nature can lead to significant cybersecurity concerns by bringing unauthorized access to home networks or leaking sensitive...

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Main Authors: Gokhan Ozogur, Zeynep Gurkas-Aydin, Mehmet Ali Erturk
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/5/2802
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author Gokhan Ozogur
Zeynep Gurkas-Aydin
Mehmet Ali Erturk
author_facet Gokhan Ozogur
Zeynep Gurkas-Aydin
Mehmet Ali Erturk
author_sort Gokhan Ozogur
collection DOAJ
description The smart TV ecosystem is rapidly expanding, allowing developers to publish their applications on TV markets to provide a wide array of services to TV users. However, this open nature can lead to significant cybersecurity concerns by bringing unauthorized access to home networks or leaking sensitive information. In this study, we focus on the security of Android TVs by developing a lightweight malware detection model specifically for these devices. We collected various Android TV applications from different markets and injected malicious payloads into benign applications to create Android TV malware, which is challenging to find on the market. We proposed a machine learning approach to detecting malware and evaluated our model. We compared the performance of nine classifiers and optimized the hyperparameters. Our findings indicated that the model performed well in rare malware cases on Android TVs. The most successful model classified malware with an F1-Score of 0.9789 in 0.1346 milliseconds per application.
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issn 2076-3417
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series Applied Sciences
spelling doaj-art-a13bcb8490c0495b89b5e929b99b84692025-08-20T02:57:41ZengMDPI AGApplied Sciences2076-34172025-03-01155280210.3390/app15052802Is Malware Detection Needed for Android TV?Gokhan Ozogur0Zeynep Gurkas-Aydin1Mehmet Ali Erturk2R&D Lab, Arcelik A.S., Istanbul 34528, TurkeyDepartment of Computer Engineering, Istanbul University-Cerrahpasa, Istanbul 34320, TurkeySchool of Computing, Engineering & The Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UKThe smart TV ecosystem is rapidly expanding, allowing developers to publish their applications on TV markets to provide a wide array of services to TV users. However, this open nature can lead to significant cybersecurity concerns by bringing unauthorized access to home networks or leaking sensitive information. In this study, we focus on the security of Android TVs by developing a lightweight malware detection model specifically for these devices. We collected various Android TV applications from different markets and injected malicious payloads into benign applications to create Android TV malware, which is challenging to find on the market. We proposed a machine learning approach to detecting malware and evaluated our model. We compared the performance of nine classifiers and optimized the hyperparameters. Our findings indicated that the model performed well in rare malware cases on Android TVs. The most successful model classified malware with an F1-Score of 0.9789 in 0.1346 milliseconds per application.https://www.mdpi.com/2076-3417/15/5/2802cybersecurityAndroid TVmalware detection
spellingShingle Gokhan Ozogur
Zeynep Gurkas-Aydin
Mehmet Ali Erturk
Is Malware Detection Needed for Android TV?
Applied Sciences
cybersecurity
Android TV
malware detection
title Is Malware Detection Needed for Android TV?
title_full Is Malware Detection Needed for Android TV?
title_fullStr Is Malware Detection Needed for Android TV?
title_full_unstemmed Is Malware Detection Needed for Android TV?
title_short Is Malware Detection Needed for Android TV?
title_sort is malware detection needed for android tv
topic cybersecurity
Android TV
malware detection
url https://www.mdpi.com/2076-3417/15/5/2802
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AT zeynepgurkasaydin ismalwaredetectionneededforandroidtv
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