Reliable aggregation on network traffic for web based knowledge discovery

Yu, Shui, James, Simon, Yonghong, Tian and Dou, Wanchun 2012, Reliable aggregation on network traffic for web based knowledge discovery, in Reliable knowledge discovery, Springer, New York, NY, pp.149-159.

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Title Reliable aggregation on network traffic for web based knowledge discovery
Author(s) Yu, Shui
James, Simon
Yonghong, Tian
Dou, Wanchun
Title of book Reliable knowledge discovery
Editor(s) Dai, Honghua
Liu, James N. K.
Smirnov, Evgueni
Publication date 2012
Chapter number 8
Total chapters 17
Start page 149
End page 159
Total pages 11
Publisher Springer
Place of Publication New York, NY
Summary The web is a rich resource for information discovery, as a result web mining is a hot topic. However, a reliable mining result depends on the reliability of the data set. For every single second, the web generate huge amount of data, such as web page requests, file transportation. The data reflect human behavior in the cyber space and therefore valuable for our analysis in various disciplines, e.g. social science, network security. How to deposit the data is a challenge. An usual strategy is to save the abstract of the data, such as using aggregation functions to preserve the features of the original data with much smaller space. A key problem, however is that such information can be distorted by the presence of illegitimate traffic, e.g. botnet recruitment scanning, DDoS attack traffic, etc. An important consideration in web related knowledge discovery then is the robustness of the aggregation method , which in turn may be affected by the reliability of network traffic data. In this chapter, we first present the methods of aggregation functions, and then we employe information distances to filter out anomaly data as a preparation for web data mining.
ISBN 1461419026
9781461419020
Language eng
Field of Research 080503 Networking and Communications
Socio Economic Objective 890101 Fixed Line Data Networks and Services
HERDC Research category B1 Book chapter
Copyright notice ©2012, Springer Science+Business Media, LLC
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044750

Document type: Book Chapter
Collections: School of Information Technology
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