A dynamic subspace anomaly detection method using generic algorithm for streaming network data
Edited book (chapter)
Chapter Title | A dynamic subspace anomaly detection method using generic algorithm for streaming network data |
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Book Chapter Category | Edited book (chapter) |
ERA Publisher ID | 2177 |
Book Title | Handbook of research on emerging developments in data privacy |
Authors | Zhang, Ji (Author) and Li, Hongzhou (Author) |
Editors | Gupta, Manish |
Page Range | 403-425 |
Series | Advances in Information Security Privacy, and Ethics |
Chapter Number | 18 |
Number of Pages | 23 |
Year | 2015 |
Publisher | IGI Global |
Place of Publication | Hershey, PA. United States |
ISBN | 9781466673816 |
9781466673823 | |
Digital Object Identifier (DOI) | https://doi.org/10.4018/978-1-4666-7381-6.ch018 |
Web Address (URL) | http://www.igi-global.com/book/handbook-research-emerging-developments-data/115494#table-of-contents |
Abstract | A great deal of research attention has been paid to data mining on data streams in recent years. In this chapter, the authors carry out a case study of anomaly detection in large and high-dimensional network connection data streams using Stream Projected Outlier deTector (SPOT) that is proposed in Zhang et al. (2009) to detect anomalies from data streams using subspace analysis. SPOT is deployed on 1999 KDD CUP anomaly detection application. Innovative approaches for training data generation, anomaly classification, false positive reduction, and adoptive detection subspace generation are proposed in this chapter as well. Experimental results demonstrate that SPOT is effective and efficient in detecting anomalies from network data streams and outperforms existing anomaly detection methods. |
Keywords | anomaly detection; data generation |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
400602. Data communications | |
460499. Cybersecurity and privacy not elsewhere classified | |
Public Notes | © 2015 IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. |
Byline Affiliations | School of Agricultural, Computational and Environmental Sciences |
Guilin University of Electronic Technology, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q2x63/a-dynamic-subspace-anomaly-detection-method-using-generic-algorithm-for-streaming-network-data
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