HTTP-sCAN: Detecting HTTP-flooding attack by modeling multi-features of web browsing behavior from noisy web-logs

2015 ◽  
Vol 12 (2) ◽  
pp. 118-128 ◽  
Author(s):  
Jin Wang ◽  
Min Zhang ◽  
Xiaolong Yang ◽  
Keping Long ◽  
Jie Xu
2008 ◽  
pp. 2004-2021
Author(s):  
Jenq-Foung Yao ◽  
Yongqiao Xiao

Web usage mining is to discover useful patterns in the web usage data, and the patterns provide useful information about the user’s browsing behavior. This chapter examines different types of web usage traversal patterns and the related techniques used to uncover them, including Association Rules, Sequential Patterns, Frequent Episodes, Maximal Frequent Forward Sequences, and Maximal Frequent Sequences. As a necessary step for pattern discovery, the preprocessing of the web logs is described. Some important issues, such as privacy, sessionization, are raised, and the possible solutions are also discussed.


2004 ◽  
pp. 335-358 ◽  
Author(s):  
Yongqiao Xiao ◽  
Jenq-Foung (J.F.) Yao

Web usage mining is to discover useful patterns in the web usage data, and the patterns provide useful information about the user’s browsing behavior. This chapter examines different types of web usage traversal patterns and the related techniques used to uncover them, including Association Rules, Sequential Patterns, Frequent Episodes, Maximal Frequent Forward Sequences, and Maximal Frequent Sequences. As a necessary step for pattern discovery, the preprocessing of the web logs is described. Some important issues, such as privacy, sessionization, are raised, and the possible solutions are also discussed.


2005 ◽  
Vol 31 (5) ◽  
pp. 433-445 ◽  
Author(s):  
Carolyn Y. Wei ◽  
Mary B. Evans ◽  
Matthew Eliot ◽  
Jennifer Barrick ◽  
Brandon Maust ◽  
...  

2013 ◽  
Vol 7 (4) ◽  
pp. 1-28 ◽  
Author(s):  
Luis A. Leiva ◽  
Roberto Vivó

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