Results 11 to 20 of about 11,847 (201)
SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System [PDF]
IEEE Access, 2018 For the last few years, Android is known to be the most widely used operating system and this rapidly increasing popularity has attracted the malware developer's attention.
Saba Arshad +5 more
doaj +3 more sources
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 +5 more
doaj +3 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 ...
Ya Pan +3 more
doaj +3 more sources
Automated Android Malware Detection Using User Feedback. [PDF]
Sensors (Basel), 2022 The widespread usage of mobile devices and their seamless adaptation to each user’s needs through useful applications (apps) makes them a prime target for malware developers. Malware is software built to harm the user, e.g., to access sensitive user data, such as banking details, or to hold data hostage and block user access. These apps are distributed
Duque J +4 more
europepmc +5 more sources
The rise of obfuscated Android malware and impacts on detection methods [PDF]
PeerJ Computer Science, 2022 The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious
Wael F. Elsersy +2 more
doaj +2 more sources
Android Malware Category and Family Identification Using Parallel Machine Learning [PDF]
Journal of Information Technology Management, 2022 Android malware is one of the most dangerous threats on the Internet. It has been on the rise for several years. As a result, it has impacted many applications such as healthcare, banking, transportation, government, e-commerce, etc.
Ahmed Hashem El Fiky +2 more
doaj +1 more source
Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data [PDF]
SensorsAndroid malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
Mehwish Naseer +6 more
doaj +2 more sources
Trends in Android Malware Detection [PDF]
Journal of Digital Forensics, Security and Law, 2013 This paper analyzes different Android malware detection techniques from several research papers, some of these techniques are novel while others bring a new perspective to the research work done in the past. The techniques are of various kinds ranging from detection using host based frameworks and static analysis of executable to feature extraction and
Kaveh Shaerpour +2 more
openaire +4 more sources
Deep Android Malware Detection [PDF]
Proceedings of the Seventh ACM on Conference on Data and Application Security and Privacy, 2017 In this paper, we propose a novel android malware detection system that uses a deep convolutional neural network (CNN). Malware classification is performed based on static analysis of the raw opcode sequence from a disassembled program. Features indicative of malware are automatically learned by the network from the raw opcode sequence thus removing ...
McLaughlin, Niall; id_orcid 0000-0002-0917-9145 +10 more
openaire +4 more sources
Applied Sciences, 2022 As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware.
Abimbola G. Akintola +9 more
doaj +1 more source