[HTML][HTML] An ensemble approach based on fuzzy logic using machine learning classifiers for android malware detection

İ Atacak - Applied Sciences, 2023 - mdpi.com
In this study, a fuzzy logic-based dynamic ensemble (FL-BDE) model was proposed to
detect malware exposed to the Android operating system. The FL-BDE model contains a …

[HTML][HTML] Android malware category detection using a novel feature vector-based machine learning model

HHR Manzil, S Manohar Naik - Cybersecurity, 2023 - Springer
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 …

[HTML][HTML] FSDroid:-A feature selection technique to detect malware from Android using Machine Learning Techniques: FSDroid

A Mahindru, AL Sangal - Multimedia Tools and Applications, 2021 - Springer
With the recognition of free apps, Android has become the most widely used smartphone
operating system these days and it naturally invited cyber-criminals to build malware …

Analyzing and comparing the effectiveness of various machine learning algorithms for Android malware detection

MS Akhtar - Advances in Mobile Learning Educational Research, 2023 - syncsci.com
Android is the most extensively adopted mobile operating system in the world. The free third-
party programmes that may be downloaded and installed contribute to this success by …

MalDetect: A classifier fusion approach for detection of android malware

M Dhalaria, E Gandotra - Expert Systems with Applications, 2024 - Elsevier
Android has been a significant target of malware applications due to the exponential growth
of mobile devices. This may result in severe threats to Android users such as financial loss …

Hybrid classification of Android malware based on fuzzy clustering and the gradient boosting machine

AA Taha, SJ Malebary - Neural Computing and Applications, 2021 - Springer
The widespread use of smartphones in recent years has led to a significant rise in the
sophistication and number of Android malicious applications (apps) targeting smartphone …

Iterative classifier fusion system for the detection of Android malware

JH Abawajy, A Kelarev - IEEE Transactions on Big Data, 2017 - ieeexplore.ieee.org
Malicious software (malware) pose serious challenges for security of big data. The number
and complexity of malware targeting Android devices have been exponentially increasing …

[HTML][HTML] A client/server malware detection model based on machine learning for android devices

A Fournier, F El Khoury, S Pierre - IoT, 2021 - mdpi.com
The rapid adoption of Android devices comes with the growing prevalence of mobile
malware, which leads to serious threats to mobile phone security and attacks private …

[PDF][PDF] Intelligent hybrid approach for Android malware detection based on permissions and API calls

A Altaher, OM Barukab - … Journal of Advanced Computer Science and …, 2017 - academia.edu
Android malware is rapidly becoming a potential threat to users. The number of Android
malware is growing exponentially; they become significantly sophisticated and cause …

[PDF][PDF] Empirical study on intelligent android malware detection based on supervised machine learning

TAA Abdullah, W Ali… - International Journal of …, 2020 - pdfs.semanticscholar.org
Android operating system in the market makes these devices the first target for malicious
applications. In recent years, several Android malware applications were developed to …