Title :
Comparative Evaluation of Anomaly Detection Techniques for Sequence Data
Author :
Chandola, Varun ; Mithal, Varun ; Kumar, Vipin
Author_Institution :
Univ. of Minnesota, Minneapolis, MN
Abstract :
We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.
Keywords :
security of data; anomaly detection technique; artificially generated data set; publicly available data set; sequence data; Automata; Data mining; Hidden Markov models; Intrusion detection; Kernel; Nearest neighbor searches; Object detection; Performance evaluation; Postal services; Testing; Anomaly Detection; Sequences;
Conference_Titel :
Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-0-7695-3502-9
DOI :
10.1109/ICDM.2008.151
