A comprehensive survey on deep learning based malware detection techniques

M Gopinath, SC Sethuraman - Computer Science Review, 2023 - Elsevier
Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …

A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

M Macas, C Wu, W Fuertes - Computer Networks, 2022 - Elsevier
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …

An effective end-to-end android malware detection method

H Zhu, H Wei, L Wang, Z Xu, VS Sheng - Expert Systems with Applications, 2023 - Elsevier
Android has rapidly become the most popular mobile operating system because of its open
source, rich hardware selectivity, and millions of applications (Apps). Meanwhile, the open …

An enhanced deep learning neural network for the detection and identification of android malware

P Musikawan, Y Kongsorot, I You… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Android-based mobile devices have attracted a large number of users because they are
easy to use and possess a wide range of capabilities. Because of its popularity, Android has …

[Retracted] A Comprehensive Review of Android Security: Threats, Vulnerabilities, Malware Detection, and Analysis

S Acharya, U Rawat… - Security and …, 2022 - Wiley Online Library
The popularity and open‐source nature of Android devices have resulted in a dramatic
growth of Android malware. Malware developers are also able to evade the detection …

[HTML][HTML] Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey

F Nawshin, R Gad, D Unal, AK Al-Ali… - Computers and Electrical …, 2024 - Elsevier
Mobile devices have become an essential element in our day-to-day lives. The chances of
mobile attacks are rapidly increasing with the growing use of mobile devices. Exploiting …

Android malware detection methods based on convolutional neural network: A survey

L Shu, S Dong, H Su, J Huang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Android malware detection (AMD) is a challenging task requiring many factors to be
considered during detection, such as feature extraction and processing, performance …

A deep learning based android malware detection system with static analysis

EC Bayazit, OK Sahingoz… - … International Congress on …, 2022 - ieeexplore.ieee.org
In recent years, smart mobile devices have become indispensable due to the availability of
office applications, the Internet, game applications, vehicle guidance or similar most of our …

GenDroid: A query-efficient black-box android adversarial attack framework

G Xu, H Shao, J Cui, H Bai, J Li, G Bai, S Liu… - Computers & …, 2023 - Elsevier
The security problems of Android applications have been gradually exposed with the
increasing popularity of the Android OS. Machine learning (ML) and deep learning (DL) …

[HTML][HTML] A review of deep learning models to detect malware in Android applications

E Mbunge, B Muchemwa, J Batani… - Cyber Security and …, 2023 - Elsevier
Android applications are indispensable resources that facilitate communication, health
monitoring, planning, data sharing and synchronization, social interaction, business and …