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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 +4 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 +4 more sources
The Evolution of Android Malware and Android Analysis Techniques [PDF]
ACM Computing Surveys, 2017 With the integration of mobile devices into daily life, smartphones are privy to increasing amounts of sensitive information. Sophisticated mobile malware, particularly Android malware, acquire or utilize such data without user consent. It is therefore essential to devise effective techniques to analyze and detect these threats. This article presents a
Lorenzo Cavallaro +2 more
exaly +5 more sources
Droiddetector: android malware characterization and detection using deep learning
Tsinghua Science and Technology, 2016 Smartphones and mobile tablets are rapidly becoming indispensable in daily life. Android has been the most popular mobile operating system since 2012. However, owing to the open nature of Android, countless malwares are hidden in a large number of benign
Zhenlong Yuan, Yibo Xue
exaly +3 more sources
Android in the Wild: A Large-Scale Dataset for Android Device Control [PDF]
Neural Information Processing Systems, 2023 There is a growing interest in device-control systems that can interpret human natural language instructions and execute them on a digital device by directly controlling its user interface. We present a dataset for device-control research, Android in the
Christopher Rawles +4 more
semanticscholar +1 more source
AutoDroid: LLM-powered Task Automation in Android [PDF]
ACM/IEEE International Conference on Mobile Computing and Networking, 2023 Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones. However, existing approaches suffer from poor scalability due to the limited language understanding ability and the non ...
Hao Wen +9 more
semanticscholar +1 more source
Continuous Learning for Android Malware Detection [PDF]
USENIX Security Symposium, 2023 Machine learning methods can detect Android malware with very high accuracy. However, these classifiers have an Achilles heel, concept drift: they rapidly become out of date and ineffective, due to the evolution of malware apps and benign apps.
Yizheng Chen +2 more
semanticscholar +1 more source
IoT-Based Android Malware Detection Using Graph Neural Network With Adversarial Defense [PDF]
IEEE Internet of Things Journal, 2023 Since the Internet of Things (IoT) is widely adopted using Android applications, detecting malicious Android apps is essential. In recent years, Android graph-based deep learning research has proposed many approaches to extract relationships from the ...
Rahul Yumlembam +3 more
semanticscholar +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
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 ...
Hashida Haidros +2 more
semanticscholar +1 more source