Malware detection method based on the control-flow construct feature of software

IET Information Security

Volumn 8, Issue 1, 2014, Pages 18-24

  Zhao, Zongqu ^a,b   Wang, Junfeng ^a   Bai, Jinrong ^a  

^a SICHUAN UNIVERSITY   (China)

^b HENAN POLYTECHNIC UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FALSE POSITIVE RATES; MALWARE DETECTION; OP-CODE SEQUENCE; OVERALL ACCURACIES; RANDOM FOREST CLASSIFIER; SOFTWARE FEATURES; SOFTWARE STRUCTURES; VECTOR SPACE MODELS;

DECISION TREES; VECTOR SPACES; VIRUSES;

COMPUTER CRIME;

EID: 84890752534     PISSN: 17518709     EISSN: 17518717     Source Type: Journal    
DOI: 10.1049/iet-ifs.2012.0289     Document Type: Article

References (22)

1. Deng, P.S., Wang, J.H., Shieh, W.G., Yen, C.P., Tung, C.T.: 'Intelligent automatic malicious code signatures extraction'. Proc. IEEE 37th Annual 2003 Int. Carnahan Conf., 2003, pp. 600-603
2. Jacob, G., Debar, H., Filiol, E.: 'Behavioral detection of malware: From a survey towards an established taxonomy', J. Comput. Virol., 2008, 4, (3), pp. 251-266
3. Kephart, J.O., Arnold, W.C.: 'Automatic extraction of computer virus signatures'. Proc. Fourth Virus Bulletin Int. Conf., 1994, pp. 178-184
4. Shabtai, A., Moskovitch, R., Elovici, Y., Glezer, C.: 'Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey', Inf. Sec. Tech. Rep., 2009, 14, (1), pp. 16-29
5. Bilar, D.: 'Opcodes as predictor for malware', Int. J. Electron. Sec. Digit. Forensics, 2007, 1, (2), pp. 156-168
6. Schultz, M.G., Eskin, E., Zadok, F., Stolfo, S.J.: 'Data mining methods for detection of new malicious executables'. Proc. Security and Privacy, 2001, pp. 38-49
7. Siddiqui, M., Wang, M.C., Lee, J.: 'Data mining methods for malware detection using instruction sequences'. Proc. 26th IASTED Int. Conf. Artificial Intelligence and Applications, 2008, pp. 358-363
8. Moskovitch, R., Feher, C., Tzachar, N., et al.: 'Unknown malcode detection using opcode representation'. Proc. European Conf. Intelligence and Security Informatics, Esbjerg, Denmark, 2008, pp. 204-215
9. Santos, I., Brezo, F., Nieves, J., et al.: 'Idea: Opcode-sequence-based malware detection', Eng. Sec. Softw. Syst., LNCS, 2010, 5965, pp. 35-43
10. Santos, I., Brezo, F., Ugarte-Pedrero, X., Bringas, P.G.: 'Opcode sequences as representation of executables for data-mining-based unknown malware detection'. Information Sciences, 2011, doi: 10.1016/j.ins.2011.08.020
11. Shabtai, A., Moskovitch, R., Feher, C., Dolev, S., Elovici, Y.: 'Detecting unknown malicious code by applying classification techniques on opcode patterns', Secur. Inf., 2012, 1, (1), pp. 1-22
12. Zhao, Z., Wang, J., Wang, C.: 'An unknown malware detection scheme based on the features of graph'. Security and Communication Networks, 2012, doi: 10.1002/sec.524
13. Mitchell, T.M.: 'Machine learning' (McGraw-Hill, USA, 1997)
14. Moskovitch, R., Stopel, D., Feher, C., Nissim, N., Elovici, Y.: 'Unknown malcode detection via text categorization and the imbalance problem'. Proc. Intelligence and Security Informatics, 2008, pp. 156-161
15. Shafiq, M., Tabish, S., Mirza, F., Farooq, M.: 'Pe-miner: Mining structural information to detect malicious executables in realtime'. Int. Symp. Recent Advances in Intrusion Detection (RAID), Lecture Notes in Computer Science, France, September 2009, pp. 121-141
16. Firoiu, L., Cohen, P.R.: 'Segmenting time series with a hybrid neural networks-hidden Markov model'. Proc. Eighteenth National Conf. Artificial Intelligence, 2002, pp. 247-252
17. Rich, C., Waters, R.C.: 'Formalizing reusable software components'. Proc. Workshop on Reusability in Programming, Newport, RI, September 1983, pp. 152-158
18. Markov, Z., Larose, D.T.: 'Data mining the Web: Uncovering patterns in Web content, structure, and usage' (Wiley-Interscience, 2007)
19. Breiman, L.: 'Bagging predictors', Mach. Learn., 1996, 24, (2), pp. 123-140
20. Breiman, L.: 'Random forests', Mach. Learn., 2001, 45, (1), pp. 5-32
21. http://vx.netlux.org/vl.php, accessed April 2010
22. Witten, I.H., Frank, E., Hall, M.A.: 'Data Mining: Practical machine learning tools and techniques', (Morgan Kaufmann, 2011)