A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
[HTML][HTML] An in-depth review of machine learning based Android malware detection
It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …
A multimodal deep learning method for android malware detection using various features
With the widespread use of smartphones, the number of malware has been increasing
exponentially. Among smart devices, android devices are the most targeted devices by …
exponentially. Among smart devices, android devices are the most targeted devices by …
Similarity-based Android malware detection using Hamming distance of static binary features
In this paper, we develop four malware detection methods using Hamming distance to find
similarity between samples which are first nearest neighbors (FNN), all nearest neighbors …
similarity between samples which are first nearest neighbors (FNN), all nearest neighbors …
Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
A multimodal malware detection technique for Android IoT devices using various features
Internet of things (IoT) is revolutionizing this world with its evolving applications in various
aspects of life such as sensing, healthcare, remote monitoring, and so on. Android devices …
aspects of life such as sensing, healthcare, remote monitoring, and so on. Android devices …
Deep learning feature exploration for android malware detection
Android mobile devices and applications are widely deployed and used in industry and
smart city. Malware detection is one of the most powerful and effective approaches to …
smart city. Malware detection is one of the most powerful and effective approaches to …
A malware detection approach using autoencoder in deep learning
Today, in the field of malware detection, the expanding limitations of traditional detection
methods and the increasing accuracy of detection methods designed on the basis of artificial …
methods and the increasing accuracy of detection methods designed on the basis of artificial …
Static malware detection and attribution in android byte-code through an end-to-end deep system
Android reflects a revolution in handhelds and mobile devices. It is a virtual machine based,
an open source mobile platform that powers millions of smartphone and devices and even a …
an open source mobile platform that powers millions of smartphone and devices and even a …
Malicious application detection in android—a systematic literature review
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …
gadgets became an essential necessity of day-to-day life. People are using new …