Intrusion-Detection Policies for IT Security Breaches

Published Online:https://doi.org/10.1287/ijoc.1070.0222

References

  • Aguirre S. J., Hill W. H. Intrusion detection fly-off: Implications for the United States Navy. (1997) . MITRE Technical Report MTR 97W096, MITRE, McLean, VAGoogle Scholar
  • Axellson S. The base-rate fallacy and the difficulty of intrusion detection. ACM Trans. Inform. System Security (2000) 3:186–205CrossrefGoogle Scholar
  • Cavusoglu H., Raghunathan S. Configuration of detection software: A comparison of decision and game theory approaches. Decision Anal. (2004) 1:131–148LinkGoogle Scholar
  • Cavusoglu H., Mishra B., Raghunathan S. The effect of internet security breach announcements on market value: Capital market reaction for breached firms and internet security developers. Internat. J. Electronic Commerce (2004) 9:69–105CrossrefGoogle Scholar
  • Cavusoglu H., Mishra B., Raghunathan S. The value of intrusion detection systems (IDSs) in information technology (IT) security. Inform. Systems Res. (2005) 16:28–46LinkGoogle Scholar
  • Denning D. E. An intrusion detection model. IEEE Trans. Software Engrg. (1987) 13:222–232CrossrefGoogle Scholar
  • D'haeseleer P., Forrest S., Helman P. An immunological approach to change detection: Algorithms, analysis, and implications. IEEE Sympos. Security and Privacy (1996) (IEEE Press, New York) CrossrefGoogle Scholar
  • Diamond H. Minimax policies for unobservable inspections. Math. Oper. Res. (1982) 7:139–153LinkGoogle Scholar
  • Durst R., Champion T., Witten B., Miller E., Spagnuolo L. Testing and evaluating computer intrusion detection systems. Comm. ACM (1999) 42:53–61CrossrefGoogle Scholar
  • Escamilla T.Intrusion Detection: Network Security Beyond the Firewall (1998) (John Wiley & Sons, New York) Google Scholar
  • Gartner Hype cycle for information security. (2003) . Gartner Research Report, Gartner, Stamford, CTGoogle Scholar
  • Gordon L. A., Loeb M. P. Using information security as a response to competitor analysis systems. Comm. ACM (2001) 44:70–75CrossrefGoogle Scholar
  • Honeynet ProjectKnow Your Enemy: Learning about Security Threats (2004) (Addison-Wesley, Boston) Google Scholar
  • Iheagwara C. The effect of intrusion detection management methods on the return on investment. Comput. Security (2004) 23:213–228CrossrefGoogle Scholar
  • Jonsson E., Olovsson T. A quantitative model of the security intrusion process based on attacker behavior. IEEE Trans. Software Engrg. (1997) 23:235–245CrossrefGoogle Scholar
  • Kumar S., Spafford E. A pattern matching model for misuse intrusion detection. The COAST Project (1996) (Purdue University, West Lafayette, IN) Google Scholar
  • Lee W., Fan W., Miller M., Stolfo S., Zadok E. Toward cost-sensitive modeling for intrusion detection and response. J. Comput. Security (2001) 10:5–22CrossrefGoogle Scholar
  • Lippmann R. P., Fried D. J., Graf I., Haines J. W., Kendall K. R., McClung D., Weber S. E., Webster D., Wyschogrod R. K., Cunningham R. K., Zissman M. A. Evaluating intrusion detection systems: The 1998 DARPA off-line intrusion detection evaluation. Proc. 2000 DARPA Inform. Survivability Conf. Exposition (2000) (IEEE Press, Los Alamitos, CA) 12–26Google Scholar
  • Lunt T. A survey of intrusion detection systems. Comput. Security (1993) 12:405–418CrossrefGoogle Scholar
  • Moitra S., Konda S. A simulation model for managing survivability of networked information systems. (2000) . Technical Report, Carnegie Mellon Software Engineering Institute, Carnegie Mellon University, PittsburghGoogle Scholar
  • Neumann P., Porras P. Experience with emerald to date. Proc. First USENIX Workshop on Intrusion Detection and Network Monitoring (1999) Santa Clara, CA:73–80Google Scholar
  • NSS GroupIntrusion Detection Systems Group Test (2001) 2nd ed.(Oakwood House, Wennington, Cambridgeshire, UK) Google Scholar
  • Ozekici S., Pliska S. Optimal scheduling of inspections: A delayed Markov model with false positives and negatives. Oper. Res. (1991) 39:261–273LinkGoogle Scholar
  • Porras P., Kemmerer R. Penetration state transition analysis: A rule based intrusion detection approach. IEEE Eighth Annual Comput. Security Appl. Conf. (1992) (IEEE Press, Los Alamitos, CA) 220–229CrossrefGoogle Scholar
  • Porras P., Neumann P. Emerald: Event monitoring enabling responses to anomalous live disturbances. Proc. 20th National Inform. Systems Security Conf. (1997) (National Institute of Standards and Technology, Baltimore) 353–365Google Scholar
  • Puketza N., Chung M., Olsson R. O., Mukherjee B. A software platform for testing intrusion detection systems. IEEE Software (1997) 14:43–51CrossrefGoogle Scholar
  • Ross S.Introduction to Stochastic Dynamic Programming (1983) (Academic Press, New York) Google Scholar
  • Russell D., Gangemi G. T.Computer Security Basics (1992) (O'Reilly & Associates, Inc., Sebastopol, CA) Google Scholar
  • Shipley G. ISS realsecure pushes past newer IDS players. Network Comput. (1999) 10:95–111Google Scholar
  • Spitzner L.Honeypots: Tracking Hackers (2002) (Addison-Wesley, Boston) Google Scholar
  • Ulvila J., Gaffney J. A decision analysis method for evaluating computer intrusion detection systems. Decision Anal. (2004) 1:35–50LinkGoogle Scholar
  • Zamboni D., Spafford E. New directions for the AAPHID architecture. Recent Advances in Intrusion Detection (1999) (Purdue University, West Lafayette, IN) Google Scholar
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