Apply anomaly grey forecasting algorithm to cyberspace situation prediction

In recent years, much research has been devoted to the cyberspace situation awareness; nevertheless, few have investigated the case that the network traffic data collected may include missing values and sufficient network traffic data may not be acquired for privacy protection or the limitation of n...

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Vydáno v:2008 IEEE Conference on Cybernetics and Intelligent Systems s. 503 - 505
Hlavní autoři: Weisong He, Guangmin Hu, Hongmei Xiang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2008
Témata:
Anomaly Grey Forecasting
Cyberspace Situation Prediction
Data engineering
Data privacy
Entropy
Predictive models
Principal component analysis
Protection
Protocols
Technology forecasting
Telecommunication traffic
Time Distribution Mapping
Time Distribution Series
Traffic control
ISBN:1424416736, 9781424416738
ISSN:2326-8123
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Shrnutí:In recent years, much research has been devoted to the cyberspace situation awareness; nevertheless, few have investigated the case that the network traffic data collected may include missing values and sufficient network traffic data may not be acquired for privacy protection or the limitation of network storage equipment capacity. Our focus in this position paper is on introducing an anomaly grey forecasting (AGF) method for cyberspace situation prediction under less data little sample, and the experiment with Abilene network Netflow data verify this method.
ISBN:1424416736
9781424416738
ISSN:2326-8123
DOI:10.1109/ICCIS.2008.4670842