Multiple criteria intelligence tracking for detecting extremes from sequences of risk incidents

Journal of Industrial and Management Optimization

Volumn 4, Issue 3, 2008, Pages 511-533

  Lambert, James H ^a   Schulte, Benjamin L ^a   Joshi, Nilesh N ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

Anomaly detection; Critical infrastructure protection; Intelligence tracking; Multiple criteria decision analysis; Precursor analysis; Risk analysis; Statistical process control

Indexed keywords

EID: 56649123242     PISSN: 15475816     EISSN: 1553166X     Source Type: Journal    
DOI: 10.3934/jimo.2008.4.511     Document Type: Article

References (36)

1. J. Allan, R. Papka and V. Lavrenko, Research and development in information retrieval, Online new event detection and tracking, Proceedings of SIGIR '98: 21st Annual International ACM SIGIR Conference, ACM Press, New York, 37-45, 1998.
2. F. Al-Qurashi, G. Sharma, W. J. Rogers and M. S. Mannan, Application of relational chemical process safety databases for lowering mean failure rates, Process Safety Progress, 20 (2001), 280-285.
3. G. Bigi, Componentwise versus global approaches to nonsmooth multiobjective optimization, Journal of Industrial and Management Optimization 1 (2005), 21-32.
4. T. C. E. Cheng and Y. Wu, Henig eficiency of a multi-criterion supply-demand network equilibrium model, Journal of Industrial and Management Optimization 2 (2006), 269-286.
5. S. V. Crowder, Design of exponentially weighted moving average schemes, Journal of Quality Technology 21 (1989), 155-162.
6. DHS (Department of Homeland Security), Sharing Information to Protect the Economy, http://www.dhs.gov/dhspublic/display?theme=73/ &content=1375, May 12, 2005.
7. F. Esponda, S. Forrest and P. Helman, A formal framework for positive and negative detection schemes, IEEE Transactions on Systems, Man and Cybernetics, 34 (2004), 357-373.
8. T. Fawcett and F. Provost, Activity monitoring: noticing interesting changes in behavior, Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, California, (1999), 53-63.
9. M. A. Gips, Shared intelligence makes everyone smarter, Security Management, 48 (2004), 52-60.
10. Y. Y. Haimes, B. M. Horowitz, J. H. Lambert, J. R. Santos, K. G. Crowther and C. Lian, Inoperability input-output model (IIM) for interdependent infrastructure sectors. I: Theory and methodology, Journal of Infrastructure Systems, 11 (2005), 67-79.
11. Y. Y. Haimes, "Risk Modeling, Assessment and Management," 2nd edition Wiley, New Jersey, 2004.
12. Y. Y. Haimes and B. M. Horowitz, Adaptive two-player hierarchical holographic two-player game for counterterrorism intelligence analysis, Journal for Homeland Security and Emergency Management, 1, Article 302.
13. B. M. Horowitz and Y. Y. Haimes, Risk-based methodology for scenario tracking, intelligence gathering, and analysis for countering terrorism, Systems Engineering 6 (2003), 152-169.
14. H. Hoertner, P. Kafka and G. Reichart, The USNRC accident sequence precursor program: present methods and findings, Reliability Engineering and System Safety, 27 (1989), 53-76.
15. J. Hollywood, D. Snyder, K. McKay and J. Boon, "Out of the Ordinary: Finding Hidden Threats by Analyzing Unusual Behavior," Santa Monica, CA, Rand Corporation, 2004.
16. B. J. Hoopes and K. P. Triantis, Efficiency performance, control charts, and process improvement, complementary measurement and evaluation, IEEE Transactions on Engineering Management, 48 (2001), 239-253.
17. J. S. Hunter, The exponentially weighted moving average, Journal of Quality Technology, 18 the (1986), 203-210.
18. H. S. Javitz and A. Valdes, The SRI IDES statistical anomaly detector, Proceedings of the IEEE Symposium on Research in Security and Privacy (1991), 316-326.
19. N. N. Joshi and J. H. Lambert, Equity metrics for the prioritization and selection of transportation projects, Transactions on Engineering Management, 54 (2007), 539-547.
20. J. H. Lambert and P. Sarda, Terrorism scenario identification by superposition infrastructure networks, Journal of Infrastructure Systems, 11 (2005), 211-220.
21. J. H. Lambert, B. L. Schulte and P. Sarda, Tracking the complexity of interactions between risk incidents and engineering systems, Journal of Systems Engineering, 8 (2005), 262-277.
22. J. M. Lucas and M. S. Saccucci, Exponentially weighted moving average control schemes: properties and enhancements with discussion and a reply by the authors, Technometrics, 32 (1990), 1-29.
23. R. L. Mason, N. D. Tracy and J. C. Young, Decomposition of the T2 for multivariate control chart interpretation, Journal of Quality Technology, 27 (1995), 99-108.
24. R. L. Mason and J. C. Young, "Multivariate Statistical Process Control with Industrial Applications," American Statistical Society and the Society for Industrial and Applied Mathematics. Philadelphia, PA, 2002.
25. C. C. Michael, Finding the vocabulary of program behavior data for anomaly detection, Proceedings of DARPA Information Survivability Conference and Exposition, 2003, 152-163.
26. Y. Michlin, B. Sedan and D. Ingman, Reliability improvement of internet web servers through statistical process control, IEEE Transactions on Reliability, 53 (2004), 551-556.
27. D. C. Montgomery, "Introduction to Statistical Quality Control," Wiley and Sons, New York (1997)
28. NAE (National Academy of Engineering), The accident precursors project: overview and recommendations, in "Accident Precursor Analysis and Management: Reducing Technological Risk Through Diligence," J. R. Phimister, V. M. Bier and H. C. Kunreuther (Eds.) National Academies Press, Washington, DC, 3-4.
29. NERC (North American Electric Reliability Council), High-voltage transmission circuit miles (230kV and above), ftp://ftp.nerc.com/pub/ sys/all_updl/docs/regional/HistoricTotalMiles.doc, (Accessed May 11, 2005).
30. NERC (North American Electric Reliability Council), System disturbance reports, http://www.nerc.com/-filez/ disturbancereports.html, (Accessed Feb. 4, 2005).
31. NERC (North American Electric Reliability Council), U.S. department of energy incident and disturbance reporting requirements, http://www.nerc.com/-dawg/append-a.html, (Accessed May 11, 2005).
32. Y. Papadopoulos, Model-based system monitoring and diagnosis of failures using state charts and fault trees, Safety, Reliability and Security of Industrial Computer Systems, 81 (2003), 325-341.
33. J. U. Tanik, G. Grimes, C. J. Sherman and V. Gurupur, An intelligent design framework proposal leveraging axiomatic design and the semantic web, Eighth World Conference on Integrated Design and Process Technology, Society for0 Design and Process Science (SDPS) Beijing, China, (June 13-17, 2005).
34. E. W. Weisstein et al., Gini coefficient, Math World-A Wolfram Web Resource, http://mathworld.wolfram.com/GiniCoefficient.html, (Accessed July 27, 2005).
35. N. Ye and Q. Chen, Computer intrusion detection through EWMA for a utocorrelated and uncorrelated data, Transactions on Reliability, 52 (2003), 75-82.
36. N. Ye, Q. Chen and C. Borror EWMA forecast of normal system activity for computer in-trusion detection, Transactions on Reliability, 53 (2004), 557-566.