A Formal Framework for Positive and Negative Detection Schemes

Fernando Esponda, Stephanie Forrest, Paul Helman

Research output: Contribution to journalArticlepeer-review

147 Scopus citations


In anomaly detection, the normal behavior of a process is characterized by a model, and deviations from the model are called anomalies. In behavior-based approaches to anomaly detection, the model of normal behavior is constructed from an observed sample of normally occurring patterns. Models of normal behavior can represent either the set of allowed patterns (positive detection) or the set of anomalous patterns (negative detection). A formal framework is given for analyzing the tradeoffs between positive and negative detection schemes in terms of the number of detectors needed to maximize coverage. For realistically sized problems, the universe of possible patterns is too large to represent exactly (in either the positive or negative scheme). Partial matching rules generalize the set of allowable (or unallowable) patterns, and the choice of matching rule affects the tradeoff between positive and negative detection. A new match rule is introduced, called r-chunks, and the generalizations induced by different partial matching rules are characterized in terms of the crossover closure. Permutations of the representation can be used to achieve more precise discrimination between normal and anomalous patterns. Quantitative results are given for the recognition ability of contiguous-bits matching together with permutations.

Original languageEnglish (US)
Pages (from-to)357-373
Number of pages17
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number1
StatePublished - Feb 2004
Externally publishedYes


  • Anamoly detection
  • Artificial immune systems
  • Intrusion detection
  • Negative detection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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