The rise of obfuscated Android malware and impacts on detection methods [PDF]
PeerJ Computer Science, 2022 The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious
Wael F. Elsersy +2 more
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FedHGCDroid: An Adaptive Multi-Dimensional Federated Learning for Privacy-Preserving Android Malware Classification [PDF]
Entropy, 2022 With the popularity of Android and its open source, the Android platform has become an attractive target for hackers, and the detection and classification of malware has become a research hotspot.
Changnan Jiang +3 more
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A Review of Android Malware Detection Approaches Based on Machine Learning
IEEE Access, 2020 Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and methods from ...
Kaijun Liu, Guoai Xu, Dawei Sun
exaly +3 more sources
A Systematic Literature Review of Android Malware Detection Using Static Analysis
IEEE Access, 2020 Android malware has been in an increasing trend in recent years due to the pervasiveness of Android operating system. Android malware is installed and run on the smartphones without explicitly prompting the users or without the user's permission, and it ...
Yong Fan, Chunrong Fang
exaly +3 more sources
Android malware category detection using a novel feature vector-based machine learning model
Cybersecurity, 2023 Malware attacks on the Android platform are rapidly increasing due to the high consumer adoption of Android smartphones. Advanced technologies have motivated cyber-criminals to actively create and disseminate a wide range of malware on Android ...
Manohar Naik S +1 more
exaly +2 more sources
OpCode-Level Function Call Graph Based Android Malware Classification Using Deep Learning [PDF]
Sensors, 2020 Due to the openness of an Android system, many Internet of Things (IoT) devices are running the Android system and Android devices have become a common control terminal for IoT devices because of various sensors on them.
Weina Niu +5 more
doaj +2 more sources
Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles [PDF]
Scientific ReportsWith the growing popularity of autonomous vehicles (AVs), confirming their safety has become a significant concern. Vehicle manufacturers have combined the Android operating system into AVs to improve consumer comfort.
Naif Almakayeel
doaj +2 more sources
Android Malware Category and Family Identification Using Parallel Machine Learning [PDF]
Journal of Information Technology Management, 2022 Android malware is one of the most dangerous threats on the Internet. It has been on the rise for several years. As a result, it has impacted many applications such as healthcare, banking, transportation, government, e-commerce, etc.
Ahmed Hashem El Fiky +2 more
doaj +1 more source
Using Machine Learning to Identify Android Malware Relying on API calling sequences and Permissions [PDF]
Journal of Computing and Communication, 2022 The revolutionary in cyber attacks, especially in smartphones are rising. The Android operating system is becoming one of the most leading operating systems. Therefore, Android malware is rising in terms of popularity.
Haytham Metwaie +6 more
doaj +1 more source
Detection and Prevention of Malware in Android Operating System
Mehran University Research Journal of Engineering and Technology, 2021 The Internet is not safe anymore, malware can be discovered anywhere on the Internet. The risk of malware has increased also due to the increasing popularity and use of Smartphones and their underlying cost-free applications. With its great market share,
Kashif Ali Dahri +2 more
doaj +1 more source