Results 31 to 40 of about 2,901,102 (167)

Machine Learning Malware Detection For Android [PDF]

, 2022
During this past year up until now, the total of malware that targets the Android operating system has increased compared to other operating systems. Therefore, an application that used the android operating system must be analyzed to detect the malware ...
Amir Muhammad Hafiz, Othman
core   +2 more sources

REVISITING AND BOOSTING STATE-OF-THE-ART ML-BASED ANDROID MALWARE DETECTORS

, 2023
Android offers plenty of services to mobile users and has gained significant popularity worldwide. The success of Android has resulted in attracting more mobile users but also malware authors.
DAOUDI, Nadia
core   +1 more source

A Lightweight Multi-Source Fast Android Malware Detection Model

Applied Sciences, 2022
Most of the current malware detection methods running on Android are based on signature and cloud technologies leading to poor protection against new types of malware. Deep learning techniques take Android malware detection to a new level.
Tao Peng, Bochao Hu, Junping Liu, Junjie Huang, Zili Zhang, Ruhan He, Xinrong Hu   +6 more
doaj   +1 more source

Review of Android Malware Detection Based on Deep Learning

IEEE Access, 2020
At present, smartphones running the Android operating system have occupied the leading market share. However, due to the Android operating system's open-source nature, Android malware has increased dramatically.
Zhiqiang Wang, Qian Liu, Yaping Chi
doaj   +1 more source

A machine learning technique for Android malicious attacks detection based on API calls [PDF]

Decision Science Letters
Android malware is widespread and it is considered as one of the most threatening attacks recently. The threat is targeting to damage access data or information or leaking them; in general, malicious software consists of viruses, worms, and ...
Mousa AL-Akhras, Saud Alghamdi, Hani Omar, Hazzaa Alshareef   +3 more
doaj   +1 more source

Android Malware Detection based on Factorization Machine [PDF]

, 2018
With the increasing popularity of Android smart phones in recent years, the amount of Android malware is growing rapidly. Due to its great threat and damage to mobile phone users, Android malware detection has become increasingly important in cyber ...
Li, Chenglin
core   +1 more source

Metaheuristics with Deep Learning Model for Cybersecurity and Android Malware Detection and Classification

Applied Sciences, 2023
Since the development of information systems during the last decade, cybersecurity has become a critical concern for many groups, organizations, and institutions.
Ashwag Albakri, Fatimah Alhayan, Nazik Alturki, Saahirabanu Ahamed, Shermin Shamsudheen   +4 more
doaj   +1 more source

Dataset Bias in Android Malware Detection

CoRR, 2022
Researchers have proposed kinds of malware detection methods to solve the explosive mobile security threats. We argue that the experiment results are inflated due to the research bias introduced by the variability of malware dataset. We explore the impact of bias in Android malware detection in three aspects, the method used to flag the ground truth ...
Yan Lin, Tianming Liu 0002, Wei Liu, Zhigaoyuan Wang, Li Li 0029, Guoai Xu, Haoyu Wang 0001   +6 more
openaire   +2 more sources

Improved chimp optimization algorithm (ICOA) feature selection and deep neural network framework for internet of things (IOT) based android malware detection

Measurement: Sensors, 2023
Internet of Things (IoT) is extensively implemented using Android applications thus detecting malicious Android apps is necessary. Malicious has been multiplying fast as a result of the growing usage of smartphones.
Tirumala Vasu G, Samreen Fiza, ATA. Kishore Kumar, V. Sowmya Devi, Ch Niranjan Kumar, Afreen Kubra   +5 more
doaj   +1 more source

vinayakumarr/Android-Malware-Detection v1

, 2019
Android malware detection using static and dynamic ...
Vinayakumar R
core   +1 more source