Results 21 to 30 of about 178,496 (217)
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
Using Machine Learning to Identify Android Malware Relying on API calling sequences and Permissions [PDF]
Journal of Computing and Communication, 2022 The revolutionary in cyber attacks, especially in smartphones are rising. The Android operating system is becoming one of the most leading operating systems. Therefore, Android malware is rising in terms of popularity.
Haytham Metwaie +6 more
doaj +1 more source
Detection and Prevention of Malware in Android Operating System
Mehran University Research Journal of Engineering and Technology, 2021 The Internet is not safe anymore, malware can be discovered anywhere on the Internet. The risk of malware has increased also due to the increasing popularity and use of Smartphones and their underlying cost-free applications. With its great market share,
Kashif Ali Dahri +2 more
doaj +1 more source
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
DroidPortrait: Android Malware Portrait Construction Based on Multidimensional Behavior Analysis
Applied Sciences, 2020 Recently, security incidents such as sensitive data leakage and video/audio hardware control caused by Android malware have raised severe security issues that threaten Android users, so thus behavior analysis and detection research researches of ...
Xin Su +5 more
doaj +1 more source
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 ...
Niall McLaughlin +10 more
openaire +3 more sources
Understanding the root of attack in android malware [PDF]
, 2018 With the rapid pace of development and change in mobile device technology and Android versions, Android malware has emerged and become a focus in current research.
Al-Ma’arif, Ahmad +4 more
core +5 more sources
Android malware category detection using a novel feature vector-based machine learning model
Cybersecurity, 2023 Malware attacks on the Android platform are rapidly increasing due to the high consumer adoption of Android smartphones. Advanced technologies have motivated cyber-criminals to actively create and disseminate a wide range of malware on Android ...
Hashida Haidros Rahima Manzil +1 more
doaj +1 more source
Orchestrating Android Malware Experiments [PDF]
2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), 2019 Experimenting with Android malware requires to manipulate a large amount of samples and to chain multiple analyses. Scripting such a sequence of analyses on a large malware dataset becomes a challenge: the analysis has to handle fails on the computer and crashes on the used smartphone, in case of dynamic analyses.
Lalande, Jean-François +2 more
openaire +2 more sources
Taxonomy of Android malware features.
, 2021 Taxonomy of Android malware features.
Juliza Mohamad Arif (11506635) +5 more
core +1 more source