Results 21 to 30 of about 4,196 (220)

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

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

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

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

Smart malware detection on Android [PDF]

Security and Communication Networks, 2015
AbstractNowadays, because of its increased popularity, Android is target to a growing number of attacks and malicious applications, with the purpose of stealing private information and consuming credit by subscribing to premium services. Most of the current commercial antivirus solutions use static signatures for malware detection, which may fail to ...
Laura Gheorghe, Bogdan Marin, Gary Gibson, Lucian Mogosanu, Razvan Deaconescu, Valentin-Gabriel Voiculescu, Mihai Carabas   +6 more
openaire   +1 more source

Trends in Android Malware Detection

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, Ali Dehghantanha, Ramlan Mahmod   +2 more
openaire   +3 more sources

A Comprehensive Review of Android Malware Detection Techniques [PDF]

E3S Web of Conferences
The 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, Kaur Harpreet, Sajid Shayan, Sagar Gaja   +3 more
doaj   +1 more source

Information security challenge of QR codes [PDF]

, 2013
The discipline of information security must adapt to new technologies and methods of interaction with those technologies. New technologies present both challenges and opportunities for the security professional, especially for areas such as digital ...
Kevin Lee, Lee, Kevin, Thompson, N., Nik Thompson, Thompson, N, Lee, K., Lee, K, Thompson, Nik   +7 more
core   +1 more source

Android Malware Detection Using BERT [PDF]

, 2022
peer reviewedIn this paper, we propose two empirical studies to (1) detect Android malware and (2) classify Android malware into families. We rst (1) reproduce the results of MalBERT using BERT models learning with Android application's manifests ...
Le Traon, Yves,, BARTEL, Alexandre, Souani, Badr,, KHANFIR, Ahmed, Bartel, Alexandre,, Khanfir, Ahmed,, LE TRAON, Yves, ALLIX, Kevin, SOUANI, Badr, Allix, Kevin,   +9 more
core   +1 more source

An antivirus API for android malware recognition

, 2022
S.77-84On the Android platform, antivirus software suffers from significant deficiencies. Due to platform limitations, it cannot access or monitor an Android device's file system, or dynamic behavior of installed apps.
Schütte, J., Kulicke, M., Fedler, R.
core   +1 more source