Prof.
Robert Moskovitch
Ben-Gurion University of the Negev -
Faculty of Engineering Sciences
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RPW BGU
BGU
General Information
Name
Prof.
Robert Moskovitch
Department
Department of Software and Information Systems Engineering
Email
robertmo@bgu.ac.il
Personal Web Site
Personal Web Site
Academic Rank
Associate Professor
General
Publications
Contact Me
Publications
Journal Articles
Conference Proceedings
Technical Report
Journal Articles
[1]
Moskovitch R.
,
Fast time intervals mining using the transitivity of temporal relations,
Knowl. Inf. Syst. (UK)
, 42, 1, 21 - 48, (2015).
[2]
Moskovitch R.
,
Classification-driven temporal discretization of multivariate time series,
Data Min. Knowl. Discov. (USA)
, 29, 4, 871 - 913, (2015).
[3]
Moskovitch R.
,
An active learning framework for efficient condition severity classification,
15th Conference on Artificial Intelligence in Medicine, AIME 2015 Proceedings: LNCS 9105
, 9105, 13 - 24, (2015).
[4]
Moskovitch R.
,
Novel active learning methods for enhanced PC malware detection in windows OS,
Expert Syst. Appl. (UK)
, 41, 13, 5843 - 57, (2014).
[5]
Moskovitch R.
,
ALPD: active learning framework for enhancing the detection of malicious PDF files,
2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC)
, 91 - 8, (2014).
[6]
Moskovitch R.
,
User identity verification via mouse dynamics,
Inf. Sci. (USA)
, 201, 19-36, (2012).
[7]
Moskovitch R.
,
Detecting unknown computer worm activity via support vector machines and active learning,
Pattern Anal. Appl. (UK)
, 15, 4, 459--475, (2012).
[8]
Moskovitch R.
,
Monitoring, analysis, and filtering system for purifying network traffic of known and unknown malicious content,
Secur. Commun. Netw. (USA)
, 4, 8, 947--965, (2011).
[9]
Stopel Dima
,
Moskovitch R.
,
Using artificial neural networks to detect unknown computer worms,
Neural Computing and Applications
, 18, 7, 663-674, (2009).
[10]
Moskovitch R.
,
Vaidurya: A multiple-ontology, concept-based, context-sensitive, clinical-guideline search engine,
The Journal of BioMedical Informatics
, 42, 1, 11-21, (2009).
[11]
Moskovitch R.
,
Detection of Malicious Code by Applying Machine Learning Classifiers on Static Features – a State-of-the-Art Survey,
Information Security Technical Report
, 14, 1, 16-29, (2009).
[12]
Moskovitch R.
,
Stopel Dima
,
Feher Clint
,
Nissim Nir
,
Japkowicz N
,
Unknown Malcode Detection and the Imbalance Problem,
Journal in Computer Virology
, 5, 4, 295-308, (2009).
[13]
Moskovitch R.
,
Detection of unknown computer worms based on behavioral classification of the host,
Computational Statistics and Data Analysis
, 52, 9, 4544 - 4566, (2008).
[14]
Moskovitch R.
,
Optimization of Fire blight scouting with a decision support system based on infection risk,
Comput. Electron. Agric. (Netherlands)
, 62, 2, 118 - 27, (2008).
[15]
Moskovitch R.
,
Application of artificial neural networks techniques to computer worm detection,
2006 International Joint Conference on Neural Networks
, 2362 - 9, (2007).
[16]
Moskovitch R.
,
Multiple hierarchical classification of free-text clinical guidelines,
Artificial Intelligence in Medicine
, 37, 3, 177-190, (2006).
[17]
Moskovitch R.
,
Identifying risk conditions for fireBlight infection using artificial neural networks based on rare events,
Computers in Agriculture and Natural Resources - Proceedings of the 4th World Congress
, 315 - 320, (2006).
[18]
Moskovitch R.
,
Helping physicians to organize guidelines within conceptual hierarchies,
Artificial Intelligence in Medicine. 10th Conference on Artificial Intelligence in Medicine, AIME 2005. Proceedings (Lecture Notes in Artificial Intelligence Vol.3581)
, 3581 LNAI, 141 - 5, (2005).
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Conference Proceedings
[1]
Moskovitch R.
,
Clustering di-graphs for continuously verifying users according to their typing patterns,2010 IEEE 26th Convention of Electrical & Electronics Engineers in Israel (IEEEI 2010), IEEE, 000445--000449, (2010).
[2]
Moskovitch R.
,
Continuous verification using keystroke dynamics,Proceedings 2010 International Conference on Computational Intelligence and Security (CIS 2010), IEEE Computer Society, 411--415, (2010).
[3]
Moskovitch R.
,
Identity Theft, Computers and Behavioral Biometrics, IEEE International Conference on Intelligence and Security Informatics (IEEE ISI-2009),2009 IEEE International Conference on Intelligence and Security Informatics (ISI), IEEE, 155 - 60, (2009).
[4]
Moskovitch R.
,
Peek Niels
,
Classificaton of ICU patients via temporal abstractions and temporal pattern mining, IDAMAP-2009, (2009).
[5]
Moskovitch R.
,
Unknown Malicious Code Detection – Practical Issues, ECIW 2008. The 7th European Conference on Information Warfare and Security, University of Plymouth, UK, June 30– July 1st, 2008, (2008).
[6]
Moskovitch R.
,
Stopel D.
,
Feher C.
,
Nissim N.
,
Unknown Malcode Detection via Text Categorization and the Imbalance Problem, ”, IEEE International Conference on Intelligence and Security Informatics (IEEE ISI-2008), Taipei, Taiwan, June 17-20, 2008, IEEE, (2008).
[7]
Moskovitch R.
,
Unknown Malcode Detection – A Chronological Evaluation, IEEE International Conference on Intelligence and Security Informatics (IEEE ISI-2008), Taipei, Taiwan, June 17-20, 2008, (2008).
[8]
Moskovitch R.
,
Feher Clint
,
Tzahar Nir
,
Berger E
,
Gitelman M
,
Dolev Shlomi
,
Unknown Malcode Detection Using OPCODE Representation, European Conference on Intelligence and Security Informatics 2008 (EuroISI08) Esbjerg, Denmark, December 3-5, 2008, (2008).
[9]
Moskovitch R.
,
Experiments with hierarchical concept-based search. MEDINFO-2007, IOS Press; 1999, (2007).
[10]
Moskovitch R.
,
Nissim Nir
,
Stopel Dima
,
Feher Clint
,
Englert Roman
,
Improving the Detection of Unknown Computer Worms Activity using Active Learning, 30th Annual German Conference on Artificial Intelligence (KI-2007), Springer, (2007).
[11]
Moskovitch R.
,
Gus Ido
,
Pluderman Shay
,
Stopel Dima
,
Parmet Y.
,
Detection of Unknown Computer Worms Activity Based on Computer Behaviour Using Data Mining, ", IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007, Honolulu, Hawaii, USA, 1-5 April 2007, (2007).
[12]
Moskovitch R.
,
Nissim N.
,
Malicious Code Detection and Acquisition Using Active Learning, ", IEEE International Conference on Intelligence and Security Informatics (IEEE ISI-2007), Rutgers University, New Jersey, USA, May 23-24, 2007, IEEE, (2007).
[13]
Moskovitch R.
,
Gus Ido
,
Pluderman Shay
,
Stopel Dima
,
Feher Clint
,
Host Based Intrusion Detection using Machine Learning, IEEE Information and Security Informatics Rutgers University, New Jersey, US, May 2007, (2007).
[14]
Moskovitch R.
,
Applying machine learning techniques for detection of malicious code in network traffic,Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, 44 - 50, (2007).
[15]
Moskovitch R.
,
Application of Artificial Neural Networks Techniques to Computer Worm Detection, IEEE World Congress on Computational Intelligence (IEEE WCCI 2006), Vancouver, BC, Canada, July 16-21, 2006,IEEE International Conference on Neural Networks - Conference Proceedings, 2362 - 2369, (2006).
[16]
Moskovitch R.
,
Vaidurya – A Concept-Based, Context-Sensitive Search Engine For Clinical Guidelines, Medinfo 2004, 5, (2004).
[17]
Moskovitch R.
,
A Multi Ontology Customized Search Query Interface for Searching Clinical Guidelines, CGP-2004, 12, (2004).
[18]
Moskovitch R.
,
DEGEL: A Hybrid, Multiple-Ontology Framework forSpecification and Retrieval of Clinical Guidelines, AIME 03, 10, (2003).
[19]
Moskovitch R.
,
Nissim Nir
,
Improving the Detection of Unknown Computer Worms Activity using Active Learning, The 11th International Conference on Information Fusion, ().
[20]
Moskovitch R.
,
Nissim N.
,
Malicious Code Detection Using Active Learning, 2nd ACM SIGKDD International Workshop on Privacy, Security, and Trust in KDD, PinKDD08, ().
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Technical Report
[1]
Shknevsky Alexander
,
Moskovitch R.
,
(24410/2017), The Semantic Adjacency Criterion in Time IntervalsMining, bgu (2017).
[2]
Moskovitch R.
,
(21843/2008), KarmaLego – An Algorithm for Fast Time Intervals Mining, (2008).
[3]
Moskovitch R.
,
(297/2004), A Framework for a Distributed, Hybrid, Multiple-Ontology Clinical-Guideline Library and Automated Guideline-Support Tools, Ben Gurion University of the Negev (2004).
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