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 | 1302 | 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 | 1161 | 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 | 1056 | 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 | 600 | 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 | 475 | 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 | 446 | 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 | 343 | 2018 |
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 | 320 | 2012 |
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 | 311 | 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 | 279 | 2017 |
Securing Android-powered mobile devices using SELinux A Shabtai, Y Fledel, Y Elovici IEEE Security & Privacy 8 (3), 36-44, 2009 | 260 | 2009 |
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 | 258 | 2010 |
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 | 233 | 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 | 214 | 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 | 207 | 2018 |
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 | 199 | 2009 |
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 | 192 | 2021 |
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 | 183 | 2010 |
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 | 170* | 2021 |
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 | 170 | 2021 |