Results 21 to 30 of about 20,046 (244)
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 +5 more
doaj +1 more source
Android Malware Characterization using Metadata and Machine Learning Techniques [PDF]
, 2017 Android Malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and meta-data to ...
Guzmán, Antonio +3 more
core +2 more sources
GSIDroid: A Suspicious Subgraph-Driven and Interpretable Android Malware Detection System. [PDF]
Sensors (Basel)Huang H, Huang W, Jiang F.
europepmc +3 more sources
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
Android Platform Malware Analysis [PDF]
International Journal of Advanced Computer Science and Applications, 2015 Mobile devices have evolved from simple devices, which are used for a phone call and SMS messages to smartphone devices that can run third party applications. Nowadays, malicious software, which is also known as malware, imposes a larger threat to these mobile devices.
Khalid Alfalqi +2 more
openaire +1 more source
A Comprehensive Review of Android Malware Detection Techniques [PDF]
E3S Web of ConferencesThe Android malware is at peak with overwhelming ubiquity of the Android Operating Systems. Malware creators have been using and devising different novel strategies to build Android apps that are malicious that are capable of creating severe damages to ...
Singh Divyanshu +3 more
doaj +1 more source
KLASIFIKASI MALWARE ANDROID DENGAN MENGGUNAKAN METODE CATBOOST ALGORITMA [PDF]
, 2023 In 2008, Android was introduced as a popular open source project due to its customizability and low hardware requirements. Mid-2021 statistics from GlobalStat Counter shows that Android dominates the mobile operating system market with 72.74%.
IRSYADUDDIN, YUSUF
core
PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting
Future Internet, 2020 Android malware has become the topmost threat for the ubiquitous and useful Android ecosystem. Multiple solutions leveraging big data and machine-learning capabilities to detect Android malware are being constantly developed.
Ajit Kumar +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 ...
McLaughlin, Niall; id_orcid 0000-0002-0917-9145 +10 more
openaire +4 more sources
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