Asaf Shabtai
Asaf Shabtai
Software and Information Systems Engineering, Telekom Innovation Labs, Ben Gurion University
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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
Kitsune: an ensemble of autoencoders for online network intrusion detection
Y Mirsky, T Doitshman, Y Elovici, A Shabtai
arXiv preprint arXiv:1802.09089, 2018
“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
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
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
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
Data leakage detection/prevention solutions
A Shabtai, Y Elovici, L Rokach, A Shabtai, Y Elovici, L Rokach
A Survey of Data Leakage Detection and Prevention Solutions, 17-37, 2012
Detecting unknown malicious code by applying classification techniques on opcode patterns
A Shabtai, R Moskovitch, C Feher, S Dolev, Y Elovici
Security Informatics 1, 1-22, 2012
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
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
Securing Android-powered mobile devices using SELinux
A Shabtai, Y Fledel, Y Elovici
IEEE Security & Privacy 8 (3), 36-44, 2009
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
Generic black-box end-to-end attack against state of the art API call based malware classifiers
I Rosenberg, A Shabtai, L Rokach, Y Elovici
Research in Attacks, Intrusions, and Defenses: 21st International Symposium …, 2018
Security testbed for Internet-of-Things devices
S Siboni, V Sachidananda, Y Meidan, M Bohadana, Y Mathov, S Bhairav, ...
IEEE transactions on reliability 68 (1), 23-44, 2018
Adversarial machine learning attacks and defense methods in the cyber security domain
I Rosenberg, A Shabtai, Y Elovici, L Rokach
ACM Computing Surveys (CSUR) 54 (5), 1-36, 2021
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
Efficient cyber attack detection in industrial control systems using lightweight neural networks and pca
M Kravchik, A Shabtai
IEEE transactions on dependable and secure computing 19 (4), 2179-2197, 2021
SoK: Security and privacy in the age of commercial drones
B Nassi, R Bitton, R Masuoka, A Shabtai, Y Elovici
2021 IEEE symposium on security and privacy (SP), 1434-1451, 2021
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