A statistical model for detecting abnormality in static-priority scheduling networks with differentiated services

Authors:
Ming Li;Wei Zhao
Affiliations:
School of Information Science & Technology, East China Normal University, Shanghai, China;Department of Computer Science, Texas A&M University, College Station, TX
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

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Abstract

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.