Results 111 to 120 of about 4,196 (220)

Large scale android malware detection

, 2018
Smartphones’ popularity and use has been increasing exponentially over the years. This also opens up the chance of damage to be done by malicious software or malware for short.
Kasim, Arief Kresnadi Ignatius
core  

AndMFC: Android Malware Family Classification Framework

, 2019
As the popularity of Android mobile operating system grows, the number of malicious software have increased extensively. Therefore, many research efforts have been done on Android malware analysis.
Ahmet Burak Can, Sercan Turker, Turker, Sercan, CAN, AHMET BURAK   +3 more
core   +1 more source

Data Drift in Android Malware Detection

2024 International Conference on Machine Learning and Cybernetics (ICMLC)
Android malware detectors are now widely implemented with machine learning algorithms, trained on large datasets of goodware and malware applications gathered at a fixed moment in time. However, as recent work showed, this domain is not stationary, causing detectors to show degrading performance over time.
Minnei, Luca, Eddoubi, Hicham, Sotgiu, Angelo, Pintor, Maura, Demontis, Ambra, Biggio, Battista   +5 more
openaire   +2 more sources

Android malware analysis

, 2012
The purpose of this report is to provide an insight to the findings gathered during the 1 year Final Year Project (FYP) period researching on Android Malware Analysis.
Chia, Liang Chuan.
core  

Explainable Machine Learning for Malware Detection on Android Applications

Information
The presence of malicious software (malware), for example, in Android applications (apps), has harmful or irreparable consequences to the user and/or the device.
Catarina Palma, Artur Ferreira, Mário Figueiredo   +2 more
doaj   +1 more source

Malware Analysis on Android

, 2021
In the XXI century, the world has witnessed the creation, development and proliferation of mobile devices until the massive usage apparent nowadays. The portability, instantaneity and ease of use that these devices offer has encouraged the great majority of the population to have one of them at arm’s length.
Puente Arribas, Daniel, Daguerre Garrido, José Ignacio, Costales de Ledesma, Ramón   +2 more
openaire   +1 more source

Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data

Sensors
Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
Mehwish Naseer, Farhan Ullah, Samia Ijaz, Hamad Naeem, Amjad Alsirhani, Ghadah Naif Alwakid, Abdullah Alomari   +6 more
doaj   +1 more source

General android malware behaviour taxonomy

, 2017
Nowadays, with rapid advancement of technology, a smartphone has significant risks as they contain sensitive information and can lead to serious security risks if it falls into unauthorised persons.
Husna Zayadi
core  

Android malware detection with MH-100K: An innovative dataset for advanced research. [PDF]

Data Brief, 2023
Bragança H, Rocha V, Barcellos L, Souto E, Kreutz D, Feitosa E.   +5 more
europepmc   +1 more source

AndroDex: Android Dex images of obfuscated malware [PDF]

With the emergence of technology and the usage of a large number of smart devices, cyber threats are increasing. Therefore, research studies have shifted their attention to detecting Android malware in recent years.
Khan, Muhammad Taimoor, Sana Aurangzeb, Aurangzeb, Sana, Muhammad Aleem, Muhammad Taimoor Khan, Sakellari, Georgia, Loukas, George, George Loukas, Georgia Sakellari, Aleem, Muhammad   +9 more
core   +1 more source