Seguir
Nir Nissim
Nir Nissim
Head of the Malware-Lab, Ben-Gurion University
Dirección de correo verificada de post.bgu.ac.il - Página principal
Título
Citado por
Citado por
Año
Dynamic malware analysis in the modern era—A state of the art survey
O Or-Meir, N Nissim, Y Elovici, L Rokach
ACM Computing Surveys (CSUR) 52 (5), 1-48, 2019
2892019
Unknown malcode detection via text categorization and the imbalance problem
R Moskovitch, D Stopel, C Feher, N Nissim, Y Elovici
2008 IEEE international conference on intelligence and security informatics …, 2008
1362008
Novel active learning methods for enhanced PC malware detection in windows OS
N Nissim, R Moskovitch, L Rokach, Y Elovici
Expert Systems with Applications 41 (13), 5843-5857, 2014
1252014
Detection of malicious PDF files and directions for enhancements: A state-of-the art survey
N Nissim, A Cohen, C Glezer, Y Elovici
Computers & Security 48, 246-266, 2015
1242015
Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory
A Cohen, N Nissim
Expert Systems with Applications 102 (Issue C), 158-178, 2018
1172018
ALDOCX: detection of unknown malicious microsoft office documents using designated active learning methods based on new structural feature extraction methodology
N Nissim, A Cohen, Y Elovici
IEEE Transactions on Information Forensics and Security 12 (3), 631-646, 2016
1062016
USB-based attacks
N Nissim, R Yahalom, Y Elovici
Computers & Security 70, 675-688, 2017
1052017
Unknown malcode detection and the imbalance problem
R Moskovitch, D Stopel, C Feher, N Nissim, N Japkowicz, Y Elovici
Journal in computer virology 5, 295-308, 2009
842009
SFEM: Structural feature extraction methodology for the detection of malicious office documents using machine learning methods
A Cohen, N Nissim, L Rokach, Y Elovici
Expert Systems with Applications 63, 324-343, 2016
792016
Detecting unknown computer worm activity via support vector machines and active learning
N Nissim, R Moskovitch, L Rokach, Y Elovici
Pattern Analysis and Applications 15, 459-475, 2012
742012
Improving the detection of unknown computer worms activity using active learning
R Moskovitch, N Nissim, D Stopel, C Feher, R Englert, Y Elovici
KI 2007: Advances in Artificial Intelligence: 30th Annual German Conference …, 2007
652007
Alpd: Active learning framework for enhancing the detection of malicious pdf files
N Nissim, A Cohen, R Moskovitch, A Shabtai, M Edry, O Bar-Ad, Y Elovici
2014 IEEE Joint Intelligence and Security Informatics Conference, 91-98, 2014
542014
Trusted System-Calls Analysis Methodology Aimed at Detection of Compromised Virtual Machines Using Sequential Mining
N Nissim, Y Lapidot, A Cohen, Y Elovici
Knowledge-Based Systems 153 (1 August 2018,), Pages 147-175, 2018
482018
Temporal probabilistic profiles for sepsis prediction in the ICU
E Sheetrit, N Nissim, D Klimov, Y Shahar
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
462019
Malicious code detection using active learning
R Moskovitch, N Nissim, Y Elovici
International Workshop on Privacy, Security, and Trust in KDD, 74-91, 2008
462008
ALDROID: efficient update of Android anti-virus software using designated active learning methods
N Nissim, R Moskovitch, O BarAd, L Rokach, Y Elovici
Knowledge and Information Systems 49, 795-833, 2016
452016
Keeping pace with the creation of new malicious PDF files using an active-learning based detection framework
N Nissim, A Cohen, R Moskovitch, A Shabtai, M Edri, O BarAd, Y Elovici
Security Informatics 5, 1-20, 2016
442016
Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments
D Nahmias, A Cohen, N Nissim, Y Elovici
Neural Networks 124, 243-257, 2020
432020
Novel set of general descriptive features for enhanced detection of malicious emails using machine learning methods
A Cohen, N Nissim, Y Elovici
Expert Systems with Applications 110, 143-169, 2018
402018
MalJPEG: Machine Learning Based Solution for the Detection of Malicious JPEG Images
A Cohen, N Nissim, Y Elovici
IEEE Access 8, 19997 - 20011, 2020
392020
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20