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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 develo** 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 …
A review on challenges and future research directions for machine learning-based intrusion detection system
Research in the field of Intrusion Detection is focused on develo** an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …
can identify network attacks. One of the important strategies is to supervise the network …
[HTML][HTML] MalDozer: Automatic framework for android malware detection using deep learning
Android OS experiences a blazing popularity since the last few years. This predominant
platform has established itself not only in the mobile world but also in the Internet of Things …
platform has established itself not only in the mobile world but also in the Internet of Things …
Deeprefiner: Multi-layer android malware detection system applying deep neural networks
As malicious behaviors vary significantly across mobile malware, it is challenging to detect
malware both efficiently and effectively. Also due to the continuous evolution of malicious …
malware both efficiently and effectively. Also due to the continuous evolution of malicious …
Application domains, evaluation data sets, and research challenges of IoT: A systematic review
We are at the brink of Internet of Things (IoT) era where smart devices and other wireless
devices are redesigning our environment to make it more correlative, flexible, and …
devices are redesigning our environment to make it more correlative, flexible, and …
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 …
A taxonomy and qualitative comparison of program analysis techniques for security assessment of android software
In parallel with the meteoric rise of mobile software, we are witnessing an alarming
escalation in the number and sophistication of the security threats targeted at mobile …
escalation in the number and sophistication of the security threats targeted at mobile …
FSDroid:-A feature selection technique to detect malware from Android using Machine Learning Techniques: FSDroid
With the recognition of free apps, Android has become the most widely used smartphone
operating system these days and it naturally invited cyber-criminals to build malware …
operating system these days and it naturally invited cyber-criminals to build malware …
Hybrid Android malware detection: A Review of heuristic-based approach
Over the last decade, numerous research efforts have been dedicated to countering
malicious mobile applications. Given its market share, Android OS has been the primary …
malicious mobile applications. Given its market share, Android OS has been the primary …
A review on android malware: Attacks, countermeasures and challenges ahead
SG Selvaganapathy… - Journal of Cyber …, 2021 - journals.riverpublishers.com
Smartphones usage have become ubiquitous in modern life serving as a double-edged
sword with opportunities and challenges in it. Along with the benefits, smartphones also …
sword with opportunities and challenges in it. Along with the benefits, smartphones also …