Improving Intrusion Prevention Models: Dual-Threshold and Dual-Filter Approaches

References

• Ahmed S., Guan Y. The inverse optimal value problem. Math. Programming (2005) 102(1):91–110Crossref, Google Scholar
• Al-Khayyal F. A., Falk J. E. Jointly constrained biconvex programming. Math. Oper. Res. (1983) 8(2):273–286Link, Google Scholar
• Anderson R. Why information security is hard—An economic perspective. Proc. 17th Annual Comput. Security Appl. Conf. (2001) New Orleans:358–365Crossref, Google Scholar
• Arora H., Mishra B. K., Raghu T. S. Autonomic-computing approach to secure knowledge management: A game-theoretic analysis. IEEE Trans. Systems, Man, Cybernetics—Part A: Systems Humans (2006) 36(3):487–497Crossref, Google Scholar
• Ashley B. K., Jackson G. L. Information assurance through defense in depth. IAnewsletter (1999) 3(2):3–7Google Scholar
• Axelsson S. The base-rate fallacy and the difficulty of intrusion detection. ACM Trans. Inform. System Security (2000) 3(3):186–205Crossref, Google Scholar
• Bace R. G.Intrusion Detection (2000) (Macmillan Technical Publishing, Indianapolis) Google Scholar
• Bennett K. P., Mangasarian O. L. Bilinear separation of two sets in n-space. Computational Optim. Appl. (1993) 2(3):207–227Crossref, Google Scholar
• Cavusoglu H., Raghunathan S. Configuration of detection software: A comparison of decision and game theory approaches. Decision Anal. (2004) 1(3):131–148Link, Google Scholar
• Cavusoglu H., Mishra B., Raghunathan S. The value of intrusion detection systems in information technology architecture. Inform. Systems Res. (2005) 16(1):28–46Link, Google Scholar
• Chen P. M., Noble B. D. When virtual is better than real. Proc. 8th Workshop on Hot Topics in Operating Systems (2001) Elmau, Germany(IEEE CS Press, Los Alamitos, CA) 133–138Crossref, Google Scholar
• Cohen W. W. Fast effective rule induction. Proc. 12th Internat. Conf. Machine Learning (1995) Tahoe City, CA:115–123Crossref, Google Scholar
• Denning D. E. An intrusion-detection model. IEEE Trans. Software Engrg. (1987) 13(2):222–232Crossref, Google Scholar
• De Shon M. Intrusion prevention versus intrusion detection. (2002) . White paper, SecureWorks, Inc., Atlanta, http://www.netbankaudit.com/images/IPSvsIDS_White_Paper.pdfGoogle Scholar
• Endorf C., Schultz E., Mellander J.Intrusion Detection & Prevention (2004) (McGraw-Hill/Osborne, Emeryville, CA) Google Scholar
• Floudas C. A., Visweswaran V. Quadratic optimization. Handbook of Global Optimization (1995) (Kluwer, Dordrecht, The Netherlands) 217–269Crossref, Google Scholar
• Gaffney J. E., Ulvila J. W. Evaluation of intrusion detectors: A decision theory approach. Proc. IEEE Sympos. Security Privacy (2001) Oakland, CA:50–61Crossref, Google Scholar
• Konno H. A cutting plane algorithm for solving bilinear programs. Math. Programming (1976) 11:14–27Crossref, Google Scholar
• Lee W., Stolfo S. J. Data mining approaches for intrusion detection. Proc. 7th USENIX Security Sympos. (1998) San Antonio, TX(USENIX, Berkeley, CA) 79–94Google Scholar
• Lee W., Stolfo S. J., Chan P. K. Learning patterns from UNIX process execution traces for intrusion detection. Proc. AAAI97 Workshop on AI Approaches to Fraud Detection and Risk Management (1997) Providence, RI(Association for the Advancement of Artificial Intelligence, Menlo Park, CA) 50–56Google Scholar
• Lee W., Fan W., Miller M., Stolfo S. J., Zadok E. Toward cost-sensitive modeling for intrusion detection and response. J. Comput. Security (2002) 10(1/2):5–22Crossref, Google Scholar
• Lippmann R. P., Cunningham R. K., Fried D. J., Graf I., Kendall K. R., Webster S. E., Zissman M. A. Results of the DARPA 1998 off-line intrusion detection evaluation. Proc. 2nd Internat. Workshop on the Recent Adv. Intrusion Detection (RAID 99) (1999) West Lafayette, IN http://www.raid-symposium.org/raid99/PAPERS/Lippmann_DARPA.pdfGoogle Scholar
• McHugh J., Christie A., Allen J. Defending yourself: The role of intrusion detection systems. IEEE Software (2000) 17(5):42–51Crossref, Google Scholar
• Michie D., Spiegelhalter D. J., Tayor C. C.Machine Learning, Neural and Statistical Classification (1994) (Ellis Horwood, London) Google Scholar
• Nitro Data Systems, Inc. Intrusion prevention. (2004) . White paper, Nitro Data Systems, Inc., Portsmouth, NH, http://www.securitytechnet.com/resource/security/ids/NGDB.pdfGoogle Scholar
• Okena, Inc. A new approach to intrusion detection: Intrusion prevention. (2003) . White paper, Okena, Inc. (Cisco, Inc.), San Jose, CA, http://www.securitytechnet.com/resource/security/ids/IDSWhitePaper.pdfGoogle Scholar
• Parker D. B.Fighting Computer Crime (1983) (Charles Scribner's Sons, New York) Google Scholar
• Paulson L. D. Stopping intruders outside the gates. Computer (2002) 35(11):20–22Crossref, Google Scholar
• Piscitello D. Intrusion detection…or prevention? Bus. Comm. Rev. (2002) 42–45Google Scholar
• Robb D. Erecting barriers. Computerworld (2005) 39(12):42–44Google Scholar
• Ross R., Katzke S., Johnson A., Swanson M., Stoneburner G., Rogers G., Lee A. Recommended security controls for federal information systems. (2005) . Special Publication 800-53, National Institute of Standards and Technology (NIST), Technology Administration, U.S. Department of Commerce, Washington, D.C.Google Scholar
• Sequeira D. Intrusion prevention systems: Security's silver bullet? Bus. Comm. Rev. (2003) 33:36–41Google Scholar
• Stolfo S. J., Lee W., Chan P. K., Fan W., Eskin E. Data mining-based intrusion detectors: An overview of the Columbia IDS project. SIGMOD Record (2001) 30(4):5–14Crossref, Google Scholar
• Ulvila J. W., Gaffney J. E. A decision analysis method for evaluating computer intrusion detection systems. Decision Anal. (2004) 1(1):35–50Link, Google Scholar
• U.S. Joint Chiefs of Staff Information assurance through defense in depth. (2000) . Special publication, U.S. Government Printing Office, Washington, D.C.Google Scholar
• Walder B. Intrusion prevention systems (IPS). (2004) . White paper, The NSS Group, Ltd., Des Plaines, IL, http://www.nss.co.uk/WhitePapers/intrusion_prevention_systems.htmGoogle Scholar
• Warrender C., Forrest S., Pearlmutter B. Detecting intrusions using system calls: Alternative data models. Proc. 1999 IEEE Sympos. Security Privacy (1999) Oakland, CA:133–145Crossref, Google Scholar