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

An efficient unsupervised feature selection procedure through feature clustering

(2020) Xuyang Yan et al.   PATTERN RECOGNITION LETTERS

Improved real-time permission based malware detection and clustering approach using model independent pruning

(2020) Janani Thiyagarajan et al.   IET Information Security

A First Look at Privacy Analysis of COVID-19 Contact-Tracing Mobile Applications

(2020) Muhammad Ajmal Azad et al.   IEEE Internet of Things Journal

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

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

Imbalanced learning based on adaptive weighting and Gaussian function synthesizing with an application on Android malware detection

(2019) Ying Pang et al.   INFORMATION SCIENCES

Unsupervised feature selection with multi-subspace randomization and collaboration

(2019) Dong Huang et al.   KNOWLEDGE-BASED SYSTEMS

CENDroid—A cluster-ensemble classifier for detecting malicious Android applications

(2019) Shikha Badhani et al.   COMPUTERS & SECURITY

On the effectiveness of system API-related information for Android ransomware detection

(2019) Michele Scalas et al.   COMPUTERS & SECURITY

Mining nested flow of dominant APIs for detecting android malware

(2019) Shahid Alam et al.   Computer Networks

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

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

Designing privacy-aware internet of things applications

(2019) Charith Perera et al.   INFORMATION SCIENCES

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

Unsupervised feature selection for balanced clustering

(2019) Peng Zhou et al.   KNOWLEDGE-BASED SYSTEMS

MalDozer: Automatic framework for android malware detection using deep learning

(2018) ElMouatez Billah Karbab et al.   Digital Investigation

Live forensics of software attacks on cyber physical systems

(2018) Ziad A. Al-Sharif et al.   Future Generation Computer Systems-The International Journal of eScience

Machine learning based mobile malware detection using highly imbalanced network traffic

(2018) Zhenxiang Chen et al.   INFORMATION SCIENCES

DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection

(2018) Suleiman Y. Yerima et al.   IEEE Transactions on Cybernetics

A machine learning based approach for phishing detection using hyperlinks information

(2018) Ankit Kumar Jain et al.   Journal of Ambient Intelligence and Humanized Computing

Mitigation and risk factor analysis of android applications

(2018) Kavita Sharma et al.   COMPUTERS & ELECTRICAL ENGINEERING

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

(2018) Alejandro Martín et al.   Information Fusion

Android malware detection based on system call sequences and LSTM

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

Dual autoencoders features for imbalance classification problem

(2016) Wing W.Y. Ng et al.   PATTERN RECOGNITION

Identifying Android malware with system call co-occurrence matrices

(2016) Xi Xiao et al.   Transactions on Emerging Telecommunications Technologies

A review on feature selection in mobile malware detection

(2015) Ali Feizollah et al.   Digital Investigation

Android based malware detection using a multifeature collaborative decision fusion approach

(2015) Shina Sheen et al.   NEUROCOMPUTING

FlowDroid

(2014) Steven Arzt et al.   ACM SIGPLAN NOTICES

Detecting mobile malware threats to homeland security through static analysis

(2013) Seung-Hyun Seo et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS