publication . Part of book or chapter of book . Preprint . 2017

Stochastic Tools for Network Intrusion Detection

Yu, Lu; Brooks, Richard R.;
Open Access
  • Published: 21 Sep 2017
  • Publisher: Springer International Publishing
Comment: Accepted by International Symposium on Sensor Networks, Systems and Security (2017)
free text keywords: Hidden Markov model, Computer science, Job shop scheduling, Intrusion detection system, Network security, business.industry, business, Partially observable Markov decision process, Theoretical computer science, Markov model, Distributed computing, Honeypot, Markov decision process, Computer Science - Cryptography and Security
Related Organizations
Download fromView all 2 versions
Part of book or chapter of book
Provider: UnpayWall
Part of book or chapter of book
Provider: Crossref
16 references, page 1 of 2

1. Adachi, Y., Oyama, Y.: Malware analysis system using process-level virtualization. In: Proceedings of IEEE Symposium on Computers and Communications, pp. 550-556 (2009)

2. Baecher, P., Koetter, M., Dornseif, M., Freiling, F.: The nepenthes platform: An efficient approach to collect malware. In: Proceedings of the 9 th International Symposium on Recent Advances in Intrusion Detection (RAID), pp. 165-184. Springer (2006) [OpenAIRE]

3. Bakar, N., Belaton, B., Samsudin, A.: False positives reduction via intrusion alert quality framework. In: Joint IEEE Malaysia International Conference on Communications and IEEE International Conference on Networks, pp. 547-552 (2005) [OpenAIRE]

4. Baumann, R.: Originally published as part of the GCIA practical

5. Garcia-Teodoroa, P., Diaz-Verdejoa, J., Macia-Fernandeza, G., Vazquezb, E.: Anomaly-based network intrusion detection: Techniques, systems and challenges. Computer & Security 28(1 - 2), 18 - 28 (2009)

6. Lu, C., Schwier, J.M., Craven, R.M., Yu, L., Brooks, R.R., Griffin, C.: A normalized statistical metric space for hidden markov models. IEEE transactions on cybernetics 43(3), 806-819 (2013)

7. Mokube, I., Adams, M.: Honeypots: Concepts, approaches, and challenges. In: ACMSE 2007, pp. 321-325. Winston-Salem, NC (2007) [OpenAIRE]

8. Provos, N.: In: Proceedings of the 12th USENIX Security Symposium, pp. 1-14 (2004)

9. Scarfone, K., Mell, P.: Guide to Intrusion Detection and Prevention Systems (IDPS). Computer Security Division, Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD (2007). NIST special publication 800-94

10. Spitzner, L.: Honeypots: Tracking Hackers. 1st edition. Addison-Wesley, Boston,MA (2002)

11. Tung, B.: The common intrusion detection framework. (1999)

12. Yu, L.: Stochastic tools for network security: Anonymity protocol analysis and network intrusion detection. Ph.D. thesis, Clemson University (2012).

13. Yu, L., Brooks, R.: Observable subspace solution for irreducible pomdps with infinite horizon. In: Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research, p. 83. ACM (2011)

14. Yu, L., Brooks, R.R.: Applying pomdp to moving target optimization. In: Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop, p. 49. ACM (2013)

15. Yu, L., Schwier, J.M., Craven, R.M., Brooks, R.R., Griffin, C.: Inferring statistically significant hidden markov models. IEEE Transactions on Knowledge and Data Engineering 25(7), 1548- 1558 (2013)

16 references, page 1 of 2
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Part of book or chapter of book . Preprint . 2017

Stochastic Tools for Network Intrusion Detection

Yu, Lu; Brooks, Richard R.;