DocumentCode
3097452
Title
LARX: Large-Scale Anti-Phishing by Retrospective Data-Exploring Based on a Cloud Computing Platform
Author
Li, Tianyang ; Han, Fuye ; Ding, Shuai ; Chen, Zhen
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear
2011
fDate
July 31 2011-Aug. 4 2011
Firstpage
1
Lastpage
5
Abstract
Anti-phishing is an intriguing challenge for Internet users especially for online business or e-pay users. Tracking phishing is quite difficult because most victims are not instantly aware of phishing attacks until their accounts are compromised, and monetary losses occur. Most web browsers provide plug-ins to protect users from phishing websites, but a client side solution cannot provide detailed forensic information on phishing attacks. In this paper, we propose an offline phishing detection system named LARX (acronym for Large-scale Anti-phishing by Retrospective data-eXploration). LARX uses network traffic data archived at a vantage point and analyzes these data for phishing attacks. All of LARX´s phishing filtering operations use cloud computing platforms and work in parallel. As an off-line solution for phishing attack detection, LARX can be effectively scaled up to analyze a large volume of trace data when enough computing power and storage capacity are provided.
Keywords
Internet; Web sites; cloud computing; computer crime; computer forensics; computer network security; online front-ends; telecommunication traffic; transaction processing; Internet; LARX; Web browsers; Web sites; cloud computing; computing power; e-pay users; forensic information; large-scale antiphishing; monetary losses; network traffic; online business; phishing attack detection; phishing filtering operations; retrospective data-exploring; storage capacity; Cloud computing; Data processing; Forensics; Google; Security; Servers;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communications and Networks (ICCCN), 2011 Proceedings of 20th International Conference on
Conference_Location
Maui, HI
ISSN
1095-2055
Print_ISBN
978-1-4577-0637-0
Type
conf
DOI
10.1109/ICCCN.2011.6005822
Filename
6005822
Link To Document