Results 21 to 30 of about 156,914 (217)

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, Omar Shereef, Amr Ehab, Mostafa Ashaf, Seif ElDein Mohamed, Eslam Amer, Ammar Mohamed   +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, Muhammad Saleem Vighio, Baqar Ali Zardari   +2 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, Lijun Xiao, Wenjia Li, Xuchong Liu, Kuan-Ching Li, Wei Liang   +5 more
doaj   +1 more source

Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection

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, Abdullateef O. Balogun, Luiz Fernando Capretz, Hammed A. Mojeed, Shuib Basri, Shakirat A. Salihu, Fatima E. Usman-Hamza, Peter O. Sadiku, Ghaniyyat B. Balogun, Zubair O. Alanamu   +9 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, Jesús Martínez del Rincón, BooJoong Kang, Suleiman Y. Yerima, Paul Miller 0003, Sakir Sezer, Yeganeh Safaei, Erik Trickel, Ziming Zhao 0001, Adam Doupé, Gail-Joon Ahn   +10 more
openaire   +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, Xiuting Ge, Chunrong Fang, Yong Fan   +3 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, Graux, Pierre, Concepción Miranda, Tomás   +2 more
openaire   +2 more sources

Classification and Analysis of Android Malware Images Using Feature Fusion Technique

IEEE Access, 2021
The super packed functionalities and artificial intelligence (AI)-powered applications have made the Android operating system a big player in the market.
Jaiteg Singh, Deepak Thakur, Tanya Gera, Babar Shah, Tamer Abuhmed, Farman Ali   +5 more
doaj   +1 more source

Android malicious attacks detection models using machine learning techniques based on permissions [PDF]

International Journal of Data and Network Science, 2023
The Android operating system is the most used mobile operating system in the world, and it is one of the most popular operating systems for different kinds of devices from smartwatches, IoT, and TVs to mobiles and cockpits in cars.
Mousa AL-Akhras, Abdulrhman ALMohawes, Hani Omar, amer Atawneh, Samah Alhazmi   +4 more
doaj   +1 more source

A Hybrid Approach for Android Malware Detection and Family Classification.

International Journal of Interactive Multimedia and Artificial Intelligence, 2021
With the increase in the popularity of mobile devices, malicious applications targeting Android platform have greatly increased. Malware is coded so prudently that it has become very complicated to identify.
Meghna Dhalaria, Ekta Gandotra
doaj   +1 more source