Asaf Shabtai
Asaf Shabtai
Software and Information Systems Engineering, Telekom Innovation Labs, Ben Gurion University
Verified email at
Cited by
Cited by
“Andromaly”: a behavioral malware detection framework for android devices
A Shabtai, U Kanonov, Y Elovici, C Glezer, Y Weiss
Journal of Intelligent Information Systems 38 (1), 161-190, 2012
Google android: A comprehensive security assessment
A Shabtai, Y Fledel, U Kanonov, Y Elovici, S Dolev, C Glezer
IEEE Security & Privacy 8 (2), 35-44, 2010
N-baiot—network-based detection of iot botnet attacks using deep autoencoders
Y Meidan, M Bohadana, Y Mathov, Y Mirsky, A Shabtai, D Breitenbacher, ...
IEEE Pervasive Computing 17 (3), 12-22, 2018
Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey
A Shabtai, R Moskovitch, Y Elovici, C Glezer
information security technical report 14 (1), 16-29, 2009
Kitsune: an ensemble of autoencoders for online network intrusion detection
Y Mirsky, T Doitshman, Y Elovici, A Shabtai
arXiv preprint arXiv:1802.09089, 2018
Securing Android-powered mobile devices using SELinux
A Shabtai, Y Fledel, Y Elovici
IEEE Security & Privacy 8 (3), 36-44, 2009
Detecting unknown malicious code by applying classification techniques on opcode patterns
A Shabtai, R Moskovitch, C Feher, S Dolev, Y Elovici
Security Informatics 1 (1), 1-22, 2012
ProfilIoT: A machine learning approach for IoT device identification based on network traffic analysis
Y Meidan, M Bohadana, A Shabtai, JD Guarnizo, M Ochoa, ...
Proceedings of the symposium on applied computing, 506-509, 2017
Automated static code analysis for classifying android applications using machine learning
A Shabtai, Y Fledel, Y Elovici
2010 International Conference on Computational Intelligence and Security …, 2010
A survey of data leakage detection and prevention solutions
A Shabtai, Y Elovici, L Rokach
Springer Science & Business Media, 2012
Mobile malware detection through analysis of deviations in application network behavior
A Shabtai, L Tenenboim-Chekina, D Mimran, L Rokach, B Shapira, ...
Computers & Security 43, 1-18, 2014
Improving malware detection by applying multi-inducer ensemble
E Menahem, A Shabtai, L Rokach, Y Elovici
Computational Statistics & Data Analysis 53 (4), 1483-1494, 2009
Intrusion detection for mobile devices using the knowledge-based, temporal abstraction method
A Shabtai, U Kanonov, Y Elovici
Journal of Systems and Software 83 (8), 1524-1537, 2010
Google android: A state-of-the-art review of security mechanisms
A Shabtai, Y Fledel, U Kanonov, Y Elovici, S Dolev
arXiv preprint arXiv:0912.5101, 2009
Detection of unauthorized IoT devices using machine learning techniques
Y Meidan, M Bohadana, A Shabtai, M Ochoa, NO Tippenhauer, ...
arXiv preprint arXiv:1709.04647, 2017
System that provides early detection, alert, and response to electronic threats
Y Elovici, G Tachan, A Shabtai
US Patent 8,171,554, 2012
Detecting cyber attacks in industrial control systems using convolutional neural networks
M Kravchik, A Shabtai
Proceedings of the 2018 Workshop on Cyber-Physical Systems Security and …, 2018
Applying behavioral detection on android-based devices
A Shabtai, Y Elovici
International Conference on Mobile Wireless Middleware, Operating Systems …, 2010
SBMDS: an interpretable string based malware detection system using SVM ensemble with bagging
Y Ye, L Chen, D Wang, T Li, Q Jiang, M Zhao
Journal in computer virology 5 (4), 283-293, 2009
Applying machine learning techniques for detection of malicious code in network traffic
Y Elovici, A Shabtai, R Moskovitch, G Tahan, C Glezer
Annual Conference on Artificial Intelligence, 44-50, 2007
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