Results 11 to 20 of about 4,196 (220)
GPFinder: Tracking the Invisible in Android Malware [PDF]
2017 12th International Conference on Malicious and Unwanted Software (MALWARE), 2017 International audienceMalicious Android applications use clever techniques to hide their real intents from the user and avoid detection by security tools.
Mourad Leslous +7 more
core +3 more sources
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
A3CM: Automatic Capability Annotation for Android Malware
IEEE Access, 2019 Android malware poses serious security and privacy threats to the mobile users. Traditional malware detection and family classification technologies are becoming less effective due to the rapid evolution of the malware landscape, with the emerging of so ...
Junyang Qiu +6 more
doaj +2 more sources
An Analysis of Android Malware Classification Services. [PDF]
Sensors (Basel), 2021 The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples. The research community relies heavily on such labels to carry out prevalence studies of the threat ecosystem and to build datasets that are used to validate and benchmark novel ...
Rashed M, Suarez-Tangil G.
europepmc +6 more sources
, 2014 The rapid growth and development of Android-based devices has resulted in a wealth of sensitive information on mobile devices that offer minimal malware protection.
Dunham, Ken
core +2 more sources
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
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
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
Guided Retraining to Enhance the Detection of Difficult Android Malware [PDF]
, 2023 peer reviewedThe popularity of Android OS has made it an appealing target for malware developers. To evade detection, including by ML-based techniques, attackers invest in creating malware that closely resemble legitimate apps, challenging the state of ...
Allix, Kevin +3 more
core +1 more source