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Keyword

Android malware detection

Description: The identification of malicious software targeting Android devices using program analysis, behavioral signals, or computational methods.
OpenAlex ID: keywords/android-malware-detection
Drebin: Effective and Explainable Detection of Android Malware in Your Pocket
2014 · Daniel Arp, Michael Spreitzenbarth, et al. · Network and Distributed System Security Symposium · 2,331
Hey, You, Get Off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets
2012 · Yajin Zhou, Zhi Wang, et al. · Network and Distributed System Security Symposium · 716
DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android
2013 · Yousra Aafer, Wenliang Du, et al. · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · 686
DroidMat: Android Malware Detection through Manifest and API Calls Tracing
2012 · Dong-Jie Wu, Ching-Hao Mao, et al. · Asia Joint Conference on Information Security (AsiaJCIS) · 626
Significant Permission Identification for Machine-Learning-Based Android Malware Detection
2018 · Jin Li, Lichao Sun, et al. · IEEE Transactions on Industrial Informatics · 607
A Multimodal Deep Learning Method for Android Malware Detection Using Various Features
2018 · TaeGuen Kim, BooJoong Kang, et al. · IEEE Transactions on Information Forensics and Security · 518
Deep Android Malware Detection
2017 · Niall McLaughlin, Jesus Martinez del Rincon, et al. · 493
Droiddetector: android malware characterization and detection using deep learning
2016 · Zhenlong Yuan, Yongqiang Lu, et al. · Tsinghua Science & Technology · 462
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DL-Droid: Deep learning based android malware detection using real devices
2019 · Mohammed K. Alzaylaee, Suleiman Y. Yerima, et al. · Computers & Security · 443
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Apposcopy: semantics-based detection of Android malware through static analysis
2014 · Yu Feng, Saswat Anand, et al. · ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE) · 437
MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
2016 · Andrea Saracino, Daniele Sgandurra, et al. · IEEE Transactions on Dependable and Secure Computing · 434
MalDozer: Automatic framework for android malware detection using deep learning
2018 · ElMouatez Billah Karbab, Mourad Debbabi, et al. · Digital Investigation · 403
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Machine Learning for Android Malware Detection Using Permission and API Calls
2013 · Naser Peiravian, Xingquan Zhu · Proceedings - International Conference on Tools with Artificial Intelligence, TAI · 379
A Review of Android Malware Detection Approaches Based on Machine Learning
2020 · Kaijun Liu, Shengwei Xu, et al. · IEEE Access · 374
Droid-Sec
2014 · Zhenlong Yuan, Yongqiang Lu, et al. · 371
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Toward Developing a Systematic Approach to Generate Benchmark Android Malware Datasets and Classification
2018 · Arash Habibi Lashkari, Andi Fitriah A. Kadir, et al. · International Carnahan Conference on Security Technology · 358
Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection
2014 · Wei Wang, Xing Wang, et al. · IEEE Transactions on Information Forensics and Security · 348
A Machine Learning Approach to Android Malware Detection
2012 · Justin Sahs, Latifur Khan · European Intelligence and Security Informatics Conference · 346
MaMaDroid
2019 · Lucky Onwuzurike, Enrico Mariconti, et al. · ACM Transactions on Privacy and Security · 334
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Structural detection of android malware using embedded call graphs
2013 · Hugo Gascon, Fabian Yamaguchi, et al. · ACM Workshop on Artificial Intelligence and Security (AISec) · 329
A Survey of Android Malware Detection with Deep Neural Models
2020 · Junyang Qiu, Jun Zhang, et al. · ACM Computing Surveys · 322
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
2017 · Ambra Demontis, Marco Melis, et al. · IEEE Transactions on Dependable and Secure Computing · 288
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DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling
2018 · Haipeng Cai, Na Meng, et al. · IEEE Transactions on Information Forensics and Security · 287
Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network
2018 · Wei Wang, Mengxue Zhao, et al. · Journal of Ambient Intelligence and Humanized Computing · 284
PUMA: Permission Usage to Detect Malware in Android
2012 · Borja Sanz, Igor Santos, et al. · Advances in intelligent systems and computing · 273
Works count: 3,724
Citation count: 62,050
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