[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 …
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 …
Effective and efficient hybrid android malware classification using pseudo-label stacked auto-encoder
Android has become the target of attackers because of its popularity. The detection of
Android mobile malware has become increasingly important due to its significant threat …
Android mobile malware has become increasingly important due to its significant threat …
[HTML][HTML] Malware detection using deep learning and correlation-based feature selection
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …
Data poisoning attacks against machine learning algorithms
FA Yerlikaya, Ş Bahtiyar - Expert Systems with Applications, 2022 - Elsevier
For the past decade, machine learning technology has increasingly become popular and it
has been contributing to many areas that have the potential to influence the society …
has been contributing to many areas that have the potential to influence the society …
JOWMDroid: Android malware detection based on feature weighting with joint optimization of weight-mapping and classifier parameters
L Cai, Y Li, Z Xiong - Computers & Security, 2021 - Elsevier
Android malware detection is an important problem that must be urgently studied and
solved. Machine learning-based methods first extract features from applications and then …
solved. Machine learning-based methods first extract features from applications and then …
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 …
Hybrid sequence‐based Android malware detection using natural language processing
N Zhang, J Xue, Y Ma, R Zhang… - International Journal of …, 2021 - Wiley Online Library
Android platform has been the target of attackers due to its openness and increasing
popularity. Android malware has explosively increased in recent years, which poses serious …
popularity. Android malware has explosively increased in recent years, which poses serious …
Learning features from enhanced function call graphs for Android malware detection
Analyzing the runtime behaviors of Android apps is crucial for malware detection. In this
paper, we attempt to learn the behavior level features of an app from function calls. The …
paper, we attempt to learn the behavior level features of an app from function calls. The …
Constructing features for detecting android malicious applications: issues, taxonomy and directions
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …