AndroAnalyzer: android malicious software detection based on deep learning

ProDroid – An Android malware detection framework based on profile hidden Markov model

(2021) Satheesh Kumar Sasidharan et al.   Pervasive and Mobile Computing

Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines

(2021) Zhen Liu et al.   Future Generation Computer Systems-The International Journal of eScience

The rise of machine learning for detection and classification of malware: Research developments, trends and challenges

(2020) Daniel Gibert et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

End-to-end malware detection for android IoT devices using deep learning

(2020) Zhongru Ren et al.   Ad Hoc Networks

On the use of artificial malicious patterns for android malware detection

(2020) Manel Jerbi et al.   COMPUTERS & SECURITY

AppPerm Analyzer: Malware Detection System Based on Android Permissions and Permission Groups

(2020) İbrahim Alper Doğru et al.   INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING

Malware detection in industrial internet of things based on hybrid image visualization and deep learning model

(2020) Hamad Naeem et al.   Ad Hoc Networks

A TAN based hybrid model for android malware detection

(2020) Roopak Surendran et al.   Journal of Information Security and Applications

An Android mutation malware detection based on deep learning using visualization of importance from codes

(2019) Yao-Saint Yen et al.   MICROELECTRONICS RELIABILITY

Permission-Based Malware Detection System for Android Using Machine Learning Techniques

(2019) Recep Sinan Arslan et al.   INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING

DL-Droid: Deep learning based android malware detection using real devices

(2019) Mohammed K. Alzaylaee et al.   COMPUTERS & SECURITY

Similarity-based Android malware detection using Hamming distance of static binary features

(2019) Rahim Taheri et al.   Future Generation Computer Systems-The International Journal of eScience

Research on data mining of permissions mode for Android malware detection

(2018) Chao Wang et al.   Cluster Computing-The Journal of Networks Software Tools and Applications

Toward a more dependable hybrid analysis of android malware using aspect-oriented programming

(2018) Aisha I. Ali-Gombe et al.   COMPUTERS & SECURITY

MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention

(2018) Andrea Saracino et al.   IEEE Transactions on Dependable and Secure Computing

DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model

(2018) Hui-Juan Zhu et al.   NEUROCOMPUTING

SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System

(2018) Saba Arshad et al.   IEEE Access

A scalable and extensible framework for android malware detection and family attribution

(2018) Li Zhang et al.   COMPUTERS & SECURITY

Android malware detection through hybrid features fusion and ensemble classifiers: the AndroPyTool framework and the OmniDroid dataset

(2018) Alejandro Martín et al.   Information Fusion

DAPASA: Detecting Android Piggybacked Apps Through Sensitive Subgraph Analysis

(2017) Ming Fan et al.   IEEE Transactions on Information Forensics and Security

Android malware detection based on system call sequences and LSTM

(2017) Xi Xiao et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Fingerprinting Android packaging: Generating DNAs for malware detection

(2016) ElMouatez Billah Karbab et al.   Digital Investigation

Generative versus discriminative classifiers for android anomaly-based detection system using system calls filtering and abstraction process

(2016) Abdelfattah Amamra et al.   Security and Communication Networks

DroidChain: A novel Android malware detection method based on behavior chains

(2016) Zhaoguo Wang et al.   Pervasive and Mobile Computing