A Statistical Model for Detecting Abnormality in Static-Priority Scheduling Networks with Differentiated Services

  • Ming Li
  • Wei Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3802)


This paper presents a new statistical model for detecting signs of abnormality in static-priority scheduling networks with differentiated services at connection levels on a class-by-class basis. The formulas in terms of detection probability, miss probability, probabilities of classifications, and detection threshold are proposed.


Anomaly detection real-time systems traffic constraint static-priority scheduling networks differentiated services time series 


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  1. 1.
    Li, M.: An Approach to Reliably Identifying Signs of DDOS Flood Attacks based on LRD Traffic Pattern Recognition. Computer & Security 23, 549–558 (2004)CrossRefGoogle Scholar
  2. 2.
    Bettati, R., Zhao, W., Teodor, D.: Real-Time Intrusion Detection and Suppression in ATM Networks. In: Proc., the 1st USENIX Workshop on Intrusion Detection and Network Monitoring, April 1999, pp. 111–118 (1999)Google Scholar
  3. 3.
    Schultz, E.: Intrusion Prevention. Computer & Security 23, 265–266 (2004)CrossRefGoogle Scholar
  4. 4.
    Cho, S.-B., Park, H.-J.: Efficient Anomaly Detection by Modeling Privilege Flows Using Hidden Markov Model. Computer & Security 22, 45–55 (2003)CrossRefGoogle Scholar
  5. 5.
    Cho, S., Cha, S.: SAD: Web Session Anomaly Detection based on Parameter Estimation. Computer & Security 23, 312–319 (2004)CrossRefGoogle Scholar
  6. 6.
    Gong, F.: Deciphering Detection Techniques: Part III Denial of Service Detection. White Paper, McAfee Network Security Technologies Group (January 2003)Google Scholar
  7. 7.
    Sorensen, S.: Competitive Overview of Statistical Anomaly Detection. White Paper, Juniper Networks Inc. (2004),
  8. 8.
    Michiel, H., Laevens, K.: Teletraffic Engineering in a Broad-Band Era. Proc. IEEE 85, 2007–2033 (1997)CrossRefGoogle Scholar
  9. 9.
    Willinger, W., Paxson, V.: Where Mathematics Meets the Internet. Notices of the American Mathematical Society 45, 961–970 (1998)zbMATHMathSciNetGoogle Scholar
  10. 10.
    Li, M., Zhao, W., et al.: Modeling Autocorrelation Functions of Self-Similar Teletraffic in Communication Networks based on Optimal Approximation in Hilbert Space. Applied Mathematical Modelling 27, 155–168 (2003)zbMATHCrossRefGoogle Scholar
  11. 11.
    Li, M., Lim, S.C.: Modeling Network Traffic Using Cauchy Correlation Model with Long-Range Dependence. Modern Physics Letters B 19, 829–840 (2005)zbMATHCrossRefGoogle Scholar
  12. 12.
    Boudec, L., Yves, J., Patrick, T.: Network Calculus, A Theory of Deterministic Queuing Systems for the Internet. Springer, Heidelberg (2001)Google Scholar
  13. 13.
    Wang, S., Xuan, D., Bettati, R., Zhao, W.: Providing Absolute Differentiated Services for Real-Time Applications in Static-Priority Scheduling Networks. IEEE/ACM T. Networking 12, 326–339 (2004)CrossRefGoogle Scholar
  14. 14.
    Cruz, L.: A Calculus for Network Delay, Part I: Network Elements in Isolation; Part II: Network Analysis. IEEE T. Inform. Theory 37, 114–131, 132-141 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Chang, C.S.: On Deterministic Traffic Regulation and Service Guarantees: a Systematic Approach by Filtering. IEEE T. Information Theory 44, 1097–1109 (1998)zbMATHCrossRefGoogle Scholar
  16. 16.
    Estan, C., Varghese, G.: New Directions in Traffic Measurement and Accounting: Focusing on the Elephants, Ignoring the Mice. ACM T. Computer Systems 21, 270–313 (2003)CrossRefGoogle Scholar
  17. 17.
    Minei, I.: MPLS DiffServ-Aware Traffic Engineering. White Paper, Juniper Networks Inc. (2004),
  18. 18.
    Leach, J.: TBSE—An Engineering Approach to The Design of Accurate and Reliable Security Systems. Computer & Security 23, 265–266 (2004)CrossRefGoogle Scholar
  19. 19.
    Kemmerer, R.A., Vigna, G.: Intrusion Detection: a Brief History and Overview. Supplement to Computer (IEEE Security & Privacy) 35, 27–30 (2002)Google Scholar
  20. 20.
    Bendat, J.S., Piersol, A.G.: Random Data: Analysis and Measurement Procedure, 2nd edn. John Wiley & Sons, Chichester (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ming Li
    • 1
  • Wei Zhao
    • 2
  1. 1.School of Information Science & TechnologyEast China Normal UniversityShanghaiChina
  2. 2.Department of Computer ScienceTexas A&M UniversityCollege StationUSA

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