Abstract
Different from the traditional static data anomaly detection, the subjects of big data stream anomaly detection has been attracting extensive attention. Through wall human being detection with UWB radar has become popular recently due to its many merits. And it is a typical big data stream mining problem when detected human being in real time. In this paper, we proposed a statistical algorithm based on spectral method for big data stream anomaly detection. The through brick wall human detection experiment was designed and the results showed that the proposed method could detect the human being with high confidence level.
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References
Silva JA, Faria ER, Barros RC et al (2013) Data stream clustering: a survey. ACM Comput Surv 46(1):1–31 (Article 13)
Wang W, Lu D, Zhou X, Zhang B, Mu J (2013) Statistical wavelet-based anomaly detection in big data with compressive sensing. EURASIP J Wireless Commun Netw 2013:269. doi:10.1186/10.1186/1687-1499-2013-269
Singh S, Liang Q, Chen D, Sheng L (2011) Sense through wall human detection using UWB radar. EURASIP J Wireless Commun Netw 2011:20
Wang W, Zhang B, Mu J (2013) Through wall detection of human being based on SPC and wavelet packet transform by UWB radar. In: IEEE international conference on communications workshop, 6, pp 955–958
Wang W, Zhou X, Zhang B, Mu J (2013) Anomaly detection in big data from UWB radars. Secur Commun Netw 3. doi:10.1002/sec.745
Zhang B, Wang W (2013) Through-wall detection of human being with compressed UWB radar data. EURASIP J Wireless Commun Netw 2013:162
Pham D-S, Venkatesh S, Lazarescu M, Budhaditya S (2014) Anomaly detection in large-scale data stream networks. Data Min Knowl Disc 28(1):145–189
Lakhina A, Crovella M, Diot C (2004) Diagnosing network-wide traffic anomalies. In: Proceedings of the 2004 conference on applications, technologies, architectures, and protocols for computer communications, pp 219–230
Acknowledgement
The authors would love to thank Professor Qilian Liang in University of Texas at Arlington for providing the UWB radar data. This research was supported by the Tianjin Younger Natural Science Foundation (12JCQNJC00400) and National Natural Science Foundation of China (61271411).
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Yun, Y., Wang, W. (2015). Big Data Stream Anomaly Detection with Spectral Method for UWB Radar Data. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_26
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DOI: https://doi.org/10.1007/978-3-319-08991-1_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08990-4
Online ISBN: 978-3-319-08991-1
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