Intrusion detection in distributed systems using fingerprinting and massive event correlation

Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

Volumn 220, Issue , 2013, Pages 2240-2254

  Skopik, Florian ^a   Fiedler, Roman ^a  

^a AIT AUSTRIAN INSTITUTE OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

ANOMALY DETECTION; COMPLEX NETWORKS; COMPUTER VIRUSES; DISTRIBUTED COMPUTER SYSTEMS; INTRUSION DETECTION; NETWORK LAYERS; NETWORK SECURITY; PALMPRINT RECOGNITION; SOCIAL COMPUTING;

ANTIVIRUS SOFTWARES; COMPUTING PARADIGM; DETECTION APPROACH; DISTRIBUTED MONITORING; DISTRIBUTED SYSTEMS; MITIGATION STRATEGY; PROTECTION MECHANISMS; SITUATIONAL AWARENESS;

COMPUTER SYSTEM FIREWALLS;

EID: 84908283968     PISSN: 16175468     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Cristina Abad, Jed Taylor, Cigdem Sengul, William Yurcik, Yuanyuan Zhou, and Kenneth E. Rowe. Log correlation for intrusion detection: A proof of concept. In ACSAC, pages 255-264. IEEE Computer Society, 2003.
2. Emilie Lundin Barse and Erland Jonsson. Extracting attack manifestations to determine log data requirements for intrusion detection. In ACSAC, pages 158-167, 2004.
3. Leyla Bilge, Thorsten Strufe, Davide Balzarotti, and Engin Kirda. All Your Contacts Are Belong to Us: Automated Identity Theft Attacks on Social Networks. In WWW, pages 551-560. ACM, 2009.
4. Varun Chandola, Arindam Banerjee, and Vipin Kumar. Anomaly detection: A survey. ACM Comput. Surv., 41:1-58, July 2009.
5. EMC Press Release. Rsa chief rallies industry to improve trust in the digital world, after year filled with cyber attacks. http://www.emc.com/about/news/press/2012/20120228-03.htm, 2012.
6. Pedro Garcia-Teodoro et al. Anomaly-based network intrusion detection: Techniques, systems and challenges. Computers & Security, 28(1-2):18-28, 2009.
7. A. Hassanzadeh and B. Sadeghiyan. A data correlation method for anomaly detection systems using regression relations. In ICFIN, pages 242-248, 2009.
8. Christopher Kruegel, Thomas Toth, and Clemens Kerer. Decentralized event correlation for intrusion detection. In ICISC, pages 59-95. 2002.
9. Aleksandar Lazarevic, Levent Ertöz, Vipin Kumar, Aysel Ozgur, and Jaideep Srivastava. A comparative study of anomaly detection schemes in network intrusion detection. In SDM. SIAM, 2003.
10. Sin Yeung Lee, Wai Lup Low, and Pei Yuen Wong. Learning fingerprints for a database intrusion detection system. In ESORICS, pages 264-280. Springer, 2002.
11. Zhenmin Li, Jed Taylor, Elizabeth Partridge, Yuanyuan Zhou, William Yurcik, Cristina Abad, James J. Barlow, and Jeff Rosendale. Uclog: A unified, correlated logging architecture for intrusion detection. In ICTSM, 2004.
12. Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping Gong, and Youping Deng. Comparison of probabilistic boolean network and dynamic bayesian network approaches for inferring gene regulatory networks. BMC Bioinformatics, 8(S-7), 2007.
13. Biswanath Mukherjee, L. Todd Heberlein, and Karl N. Levitt. Network intrusion detection. IEEE Network, 8(3):26-41, 1994.
14. David W. Mount. Bioinformatics: sequence and genome analysis. CSHL press, 2004.
15. Florian Skopik, Zhendong Ma, Paul Smith, and Thomas Bleier. Designing a cyber attack information system for national situational awareness. In Future Security, pages 277-288, 2012.