Information Technology Reference
In-Depth Information
3. Schultz, M., Eskin, E., Zadok, F., Stolfo, S.: Data mining methods for detection
of new malicious executables. In: Proceedings of the 22 n d
IEEE Symposium on
Security and Privacy, pp. 38-49 (2001)
4. Kolter, J., Maloof, M.: Learning to detect malicious executables in the wild. In:
Proceedings of the 10 th ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining, pp. 470-478. ACM, New York (2004)
5. Zhou, Y., Inge, W.: Malware detection using adaptive data compression. In: Pro-
ceedings of the 1st ACM Workshop on Workshop on AISec, pp. 53-60. ACM, New
York (2008)
6. Santos, I., Penya, Y., Devesa, J., Bringas, P.: N-Grams-based file signatures for
malware detection. In: Proceedings of the 11 th International Conference on Enter-
prise Information Systems (ICEIS), vol. AIDSS, pp. 317-320 (2009)
7. Santos, I., Brezo, F., Nieves, J., Penya, Y.K., Sanz, B., Laorden, C., Bringas, P.G.:
Opcode-sequence-based malware detection. In: Massacci, F., Wallach, D., Zannone,
N. (eds.) ESSoS 2010. LNCS, vol. 5965, pp. 35-43. Springer, Heidelberg (2010)
8. Christodorescu, M.: Behavior-based malware detection. PhD thesis (2007)
9. Perdisci, R., Gu, G., Lee, W.: Using an ensemble of one-class svm classifiers to
harden payload-based anomaly detection systems. In: Proceedings of 6 th Inter-
national Conference on Data Mining (ICDM), pp. 488-498. IEEE, Los Alamitos
(2007)
10. Chapelle, O., Scholkopf, B., Zien, A.: Semi-supervised learning. MIT Press, Cam-
bridge (2006)
11. Zhou, D., Bousquet, O., Lal, T., Weston, J., Scholkopf, B.: Learning with local
and global consistency. In: Proceedings of the 2003 Conference Advances in Neural
Information Processing Systems, vol. 16, pp. 595-602 (2004)
12. McGill, M.J., Salton, G.: Introduction to modern information retrieval. McGraw-
Hill, New York (1983)
13. Garner, S.: Weka: The Waikato environment for knowledge analysis. In: Proceed-
ings of the New Zealand Computer Science Research Students Conference, pp.
57-64 (1995)
14. Singh, Y., Kaur, A., Malhotra, R.: Comparative analysis of regression and machine
learning methods for predicting fault proneness models. International Journal of
Computer Applications in Technology 35(2), 183-193 (2009)
15. Kang, M., Poosankam, P., Yin, H.: Renovo: A hidden code extractor for packed
executables. In: Proceedings of the 2007 ACM Workshop on Recurring Malcode,
pp. 46-53 (2007)
16. Royal, P., Halpin, M., Dagon, D., Edmonds, R., Lee, W.: Polyunpack: Automating
the hidden-code extraction of unpack-executing malware. In: Proceedings of the
22 nd Annual Computer Security Applications Conference (ACSAC), pp. 289-300
(2006)
17. Martignoni, L., Christodorescu, M., Jha, S.: Omniunpack: Fast, generic, and safe
unpacking of malware. In: Proceedings of the 23 rd Annual Computer Security
Applications Conference (ACSAC), pp. 431-441 (2007)
18. Sharif, M., Yegneswaran, V., Saidi, H., Porras, P.A., Lee, W.: Eureka: A framework
for enabling static malware analysis. In: Jajodia, S., Lopez, J. (eds.) ESORICS
2008. LNCS, vol. 5283, pp. 481-500. Springer, Heidelberg (2008)
 
Search WWH ::




Custom Search