DocumentCode :
1683990
Title :
Apriori-PrefixSpan Hybrid Approach for Automated Detection of Botnet Coordinated Attacks
Author :
Ohrui, Masayuki ; Kikuchi, Hiroaki ; Terada, Masato ; Rosyid, Nur Rohman
Author_Institution :
Dept. of Inf. Sci. & Eng., Tokai Univ., Hiratsuka, Japan
fYear :
2011
Firstpage :
92
Lastpage :
97
Abstract :
This paper aims to detect features of coordinated attacks by applying data mining techniques, Apriori and Prefix Span, to the CCC DATA set 2008-2010 which consists of the captured packets data and the downloading logs. Data mining algorithms allow us to automate detecting characteristics from large amount of data, which the conventional heuristics could not apply. Apriori a chives high recall but with false positive, while Prefix Span has high precision but low recall. Hence, we propose hybriding these algorithms. Our analysis shows the change in behavior of malware over the past 3 years.
Keywords :
data mining; invasive software; Apriori-PrefixSpan hybrid approach; CCC DATA set; automated detection; botnet coordinated attacks; data mining; malware; Accuracy; Association rules; Databases; Grippers; Malware; Servers; Apriori; Botnets; Coordinated Attacks; Malware; PrefixSpan;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network-Based Information Systems (NBiS), 2011 14th International Conference on
Conference_Location :
Tirana
ISSN :
2157-0418
Print_ISBN :
978-1-4577-0789-6
Electronic_ISBN :
2157-0418
Type :
conf
DOI :
10.1109/NBiS.2011.23
Filename :
6041909
Link To Document :
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