On the use of sketches and wavelet analysis for network anomaly detection

Authors:
Christian Callegari;Stefano Giordano;Michele Pagano;Teresa Pepe
Affiliations:
University of Pisa, Pisa, Italy;University of Pisa, Pisa, Italy;University of Pisa, Pisa, Italy;University of Pisa, Pisa, Italy
Venue:
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Year:
2010

Citing 7
Cited 4

Ten lectures on wavelets

Ten lectures on wavelets
A non-instrusive, wavelet-based approach to detecting network performance problems

IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
A signal analysis of network traffic anomalies

Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Tabulation based 4-universal hashing with applications to second moment estimation

SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
An improved data stream summary: the count-min sketch and its applications

Journal of Algorithms
Mining anomalies using traffic feature distributions

Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Extracting hidden anomalies using sketch and non Gaussian multiresolution statistical detection procedures

Proceedings of the 2007 workshop on Large scale attack defense

A scalable, efficient and informative approach for anomaly-based intrusion detection systems: theory and practice

International Journal of Network Management
Combining wavelet analysis and information theory for network anomaly detection

Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
ADMIRE: Anomaly detection method using entropy-based PCA with three-step sketches

Computer Communications
A methodological overview on anomaly detection

DataTraffic Monitoring and Analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the last few years, the number and impact of security attacks over the Internet have been continuously increasing. Since it seems impossible to guarantee complete protection to a system by means of the "classical" prevention mechanisms, the use of Intrusion Detection Systems has emerged as a key element in network security. In this paper we address the problem considering a novel technique for detecting network anomalies. Our approach is based on the combined use of sketch and wavelet analysis to reveal the anomalies present in data collected at the router level. The performance analysis, presented in this paper, demonstrates the effectiveness of the proposed method.