Nir Nissim
Nir Nissim
Head of the Malware-Lab, Ben-Gurion University
Verified email at post.bgu.ac.il - Homepage
TitleCited byYear
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
902008
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
732014
Unknown malcode detection and the imbalance problem
R Moskovitch, D Stopel, C Feher, N Nissim, N Japkowicz, Y Elovici
Journal in Computer Virology 5 (4), 295, 2009
662009
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
542015
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 (4), 459-475, 2012
492012
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
362016
Malicious code detection using active learning
R Moskovitch, N Nissim, Y Elovici
International Workshop on Privacy, Security, and Trust in KDD, 74-91, 2008
352008
Improving the detection of unknown computer worms activity using active learning
R Moskovitch, N Nissim, D Stopel, C Feher, R Englert, Y Elovici
Annual Conference on Artificial Intelligence, 489-493, 2007
342007
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
292014
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
272016
USB-based attacks
N Nissim, R Yahalom, Y Elovici
Computers & Security 70, 675-688, 2017
262017
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
252018
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), 1, 2016
212016
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 (3), 795-833, 2016
212016
An active learning framework for efficient condition severity classification
N Nissim, MR Boland, R Moskovitch, NP Tatonetti, Y Elovici, Y Shahar, ...
Conference on Artificial Intelligence in Medicine in Europe, 13-24, 2015
172015
Malicious code detection and acquisition using active learning
R Moskovitch, N Nissim, Y Elovici
2007 IEEE Intelligence and Security Informatics, 371-371, 2007
162007
Acquisition of malicious code using active learning
R Moskovitch, N Nissim, Y Elovici
Proc. 2nd Int’l Workshop on Privacy, Security, & Trust in KDD, 2008
152008
Improving condition severity classification with an efficient active learning based framework
N Nissim, MR Boland, NP Tatonetti, Y Elovici, G Hripcsak, Y Shahar, ...
Journal of biomedical informatics 61, 44-54, 2016
122016
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
112018
Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods
N Nissim, Y Shahar, Y Elovici, G Hripcsak, R Moskovitch
Artificial intelligence in medicine 81, 12-32, 2017
102017
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Articles 1–20