NADA - Network anomaly detection algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4785 LNCS, Issue , 2007, Pages 191-194

  Farraposo, Sílvia ^a   Owezarski, Philippe ^b   Monteiro, Edmundo ^c  

^a POLYTECHNIC INSTITUTE OF LEIRIA   (Portugal)

^b LAAS CNRS   (France)

^c UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

Anomaly signature; Traffic anomaly identification

Indexed keywords

ALGORITHMS; INTERNET PROTOCOLS; ITERATIVE METHODS; CLASSIFICATION (OF INFORMATION); NETWORK SECURITY; SIGNAL DETECTION;

MONITORING ENVIRONMENT; NETWORK ANOMALY DETECTION; ANOMALY SIGNATURE; BEHAVIOR-BASED; CLASSIFICATION AND IDENTIFICATIONS; DIFFERENT TIME SCALE; ITERATIVE NETWORKS; TRAFFIC ANOMALIES;

CLASSIFICATION (OF INFORMATION); ALGORITHMS;

EID: 38149030783     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75694-1_18     Document Type: Conference Paper

References (4)

1. Kim, S., Reddy, A., Vannucci, M.: Detecting Traffic Anomalies through Aggregate Analysis of Packet Header Data. In: Networking 2004, Athens (2004)
2. Lakhina, A., Crovella, M., Diot, C.: Mining Anomalies Using Traffic Feature Distributions. In: ACM SIGCOMM, Philadelphia (2005)
3. Farraposo, S., Owezarski, P., Monteiro, E.: A Multi-Scale Tomographic Algorithm for Detecting and Classifying Traffic Anomalies. In: IEEE ICC 2007, Glasgow (2007)
4. Cormode, G., Muthukrishnan, S.: What's New: Finding Significant Differences in Network Data Streams. In: IEEE/ACM Transactions on Networking, vol. 13 (2005)