Unknown malcode detection - A chronological evaluation

IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008

Volumn , Issue , 2008, Pages 267-268

  Moskovitch, Robert ^a   Feher, Clint ^a   Elovici, Yuval ^a  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

Classification algorithms; Malicious code detection

Indexed keywords

CLASSIFICATION (OF INFORMATION); CODES (STANDARDS); HEURISTIC METHODS; HEURISTIC PROGRAMMING; INTERSYMBOL INTERFERENCE; STATIC ANALYSIS;

CLASSIFICATION ALGORITHMS; INTERNATIONAL CONFERENCES; MALCODE; MALICIOUS CODE; MALICIOUS CODE DETECTION; MALICIOUS CODES; OPTIMIZED CONDITIONS; SECURITY INFORMATICS; TRAINING SETS;

CODES (SYMBOLS);

EID: 51849149887     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISI.2008.4565078     Document Type: Conference Paper

References (6)

1. Gryaznov, D. Scanners of the Year 2000: Heuritics, Proceedings of the 5th International Virus Bulletin, 1999.
2. Schultz, M., Eskin, E., Zadok, E., and Stolfo, S. (2001) Data mining methods for detection of new malicious executables, in Proceedings of the IEEE Symposium on Security and Privacy, 2001, pp. 178-184.
3. Abou-Assaleh, T., Cercone, N., Keselj, V., and Sweidan, R. (2004). N-gram Based Detection of New Malicious Code, in Proceedings of the 28th Annual International Computer Software and Applications Conference (COMPSAC04).
4. Kolter, J., and Maloof, M. (2006) Learning to Detect and Classify Malicious Executables in the Wild, Journal of Machine Learning Research 7, 2721-2744.
5. Chawla, N. V., Japkowicz, N., and Kotcz, A. (2004). Editorial: special issue on learning from imbalanced data sets. SIGKDD Explorations Newsletter 6(1):1-6.
6. Moskovitch, R., Stopel, D., Feher, C, Missim, N., Elovici, Y., Unknown Malicious Code Detection via Text Categorization and the Imbalance Problem, IEEE Intelligence and Security Informatics, Taiwan, 2008.