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 …
Machine learning-based solutions have been successfully employed for the automatic detection of malware on Android. However, machine learning models lack robustness to …
With the integration of mobile devices into daily life, smartphones are privy to increasing amounts of sensitive information. Sophisticated mobile malware, particularly Android …
S Dong, K Abbas, R Jain - IEEE Access, 2019 - ieeexplore.ieee.org
Recently, software defined networks (SDNs) and cloud computing have been widely adopted by researchers and industry. However, widespread acceptance of these novel …
P Faruki, A Bharmal, V Laxmi… - … surveys & tutorials, 2014 - ieeexplore.ieee.org
Smartphones have become pervasive due to the availability of office applications, Internet, games, vehicle guidance using location-based services apart from conventional services …
Abstract An Internet of Things (IoT) architecture generally consists of a wide range of Internet- connected devices or things such as Android devices, and devices that have more …
Modern electronic devices have become “smart” as well as omnipresent in our day-to-day lives. From small household devices to large industrial machines, smart devices have …
Context Static analysis exploits techniques that parse program source code or bytecode, often traversing program paths to check some program properties. Static analysis …
MB Mollah, MAK Azad, A Vasilakos - Journal of Network and Computer …, 2017 - Elsevier
The rapid growth of mobile computing is seriously challenged by the resource constrained mobile devices. However, the growth of mobile computing can be enhanced by integrating …