Get started
Keyword

Android malware

Description: Malicious software designed to compromise devices or data running the Android operating system, studied in mobile cybersecurity.
OpenAlex ID: keywords/android-malware
Dissecting Android Malware: Characterization and Evolution
2012 · Yajin Zhou, Xuxian Jiang · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 2,133
FlowDroid
2014 · Steven Arzt, Siegfried Rasthofer, et al. · ACM SIGPLAN Notices · 946
Crowdroid
2011 · Iker Burguera, Urko Zurutuza, et al. · 910
A survey of mobile malware in the wild
2011 · Adrienne Porter Felt, Matthew Finifter, et al. · 768
Android Security: A Survey of Issues, Malware Penetration, and Defenses
2014 · Parvez Faruki, Ammar Bharmal, et al. · IEEE Communications Surveys & Tutorials · 559
IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture
2020 · Danish Vasan, Mamoun Alazab, et al. · Computer Networks · 515
Evaluation of machine learning classifiers for mobile malware detection
2014 · Fairuz Amalina Narudin, Ali Feizollah, et al. · Soft Computing · 401
Deep Ground Truth Analysis of Current Android Malware
2017 · Fengguo Wei, Yuping Li, et al. · Lecture notes in computer science · 398
CopperDroid: Automatic Reconstruction of Android Malware Behaviors
2015 · Kimberly Tam, Salahuddin J. Khan, et al. · Network and Distributed System Security Symposium · 398
The Evolution of Android Malware and Android Analysis Techniques
2017 · Kimberly Tam, Ali Feizollah, et al. · ACM Computing Surveys · 356
PDF
Machine learning aided Android malware classification
2017 · Nikola Milosevic, Ali Dehghantanha, et al. · Computers & Electrical Engineering · 348
PDF
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection
2018 · Chen, Xiao, Li, Chaoran, et al. · arXiv (Cornell University) · 328
PDF
Dynamic Android Malware Category Classification using Semi-Supervised Deep Learning
2020 · Samaneh Mahdavifar, Andi Fitriah Abdul Kadir, et al. · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · 324
Intriguing Properties of Adversarial ML Attacks in the Problem Space
2020 · Fabio Pierazzi, Feargus Pendlebury, et al. · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 307
PDF
ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors
2014 · Martina Lindorfer, Matthias Neugschwandtner, et al. · 304
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
2016 · Grosse, Kathrin, Papernot, Nicolas, et al. · arXiv (Cornell University) · 299
PDF
A comprehensive survey on deep learning based malware detection techniques
2022 · Gopinath M., Sibi Chakkaravarthy Sethuraman · Computer Science Review · 278
Execute This! Analyzing Unsafe and Malicious Dynamic Code Loading in Android Applications
2014 · Sebastian Poeplau, Yanick Fratantonio, et al. · Network and Distributed System Security Symposium · 265
Mobile-sandbox
2013 · Michael Spreitzenbarth, Felix Freiling, et al. · ACM Symposium on Applied Computing · 250
Droid Analytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware
2013 · Min Zheng, Mingshen Sun, et al. · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · 246
PDF
Android Malware Familial Classification and Representative Sample Selection via Frequent Subgraph Analysis
2018 · Ming Fan, Jun Liu, et al. · IEEE Transactions on Information Forensics and Security · 233
Evading android runtime analysis via sandbox detection
2014 · Timothy Vidas, Nicolas Christin · ACM Symposium on Information, Computer and Communications Security · 232
PDF
Dendroid: A text mining approach to analyzing and classifying code structures in Android malware families
2013 · Guillermo Suarez-Tangil, Juan E. Tapiador, et al. · Expert Systems with Applications · 231
PDF
IntelliDroid: A Targeted Input Generator for the Dynamic Analysis of Android Malware
2016 · Michelle Y. Wong, David Lie · Network and Distributed System Security Symposium · 226
PDF
Fed-IIoT: A Robust Federated Malware Detection Architecture in Industrial IoT
2020 · Rahim Taheri, Mohammad Shojafar, et al. · IEEE Transactions on Industrial Informatics · 216
Works count: 2,216
Citation count: 32,450
Year
Topic
Type