A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential change-point detection methods

By Alexander G. Tartakovsky, Boris L. Rozovskii, Rudolf B. Blazek, Hongjoon Kim. IEEE Transactions on Signal Processing, 2006

299 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4a7958c96feee0a88de4471fea27a81b090f7795

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. C. L'evy-Leduc
2. Alexandre Lung-Yut-Fong
3. Olivier Capp'e
4. R´emi Munos
5. Nicolas Vayatis
6. Laurent Oudre
7. Charles Truong
8. David S. Matteson

In Computer Networks and Communications

1. Olivier Capp'e

In Statistics and Probability

1. C. L'evy-Leduc
2. Alexandre Lung-Yut-Fong
3. Olivier Capp'e
4. Nicolas Vayatis
5. Laurent Oudre
6. Charles Truong
7. David S. Matteson
8. Nicholas A. James

Citations in the corpus

• Homogeneity and change-point detection tests for multivariate data using rank statistics (2011, background): “…are instrumental in applications that range from the surveillance of industrial processes (Basseville and Nikiforov, 1993), to computer security (Tartakovsky et al., 2006; Lévy-Leduc and Roueff, 2009), processing of audiovisual data (Désobry et al., 2005), financial and econometric modelling…”
• Data-efficient minimax quickest change detection (2012, unknown): “3) Computer network security: Algorithms for quickest change detection have been applied in the detection of abnormal behavior in computer networks due to security breaches [62], [63], [64].”