DocumentCode :
2965713
Title :
Enhancing Collaborative Spam Detection with Bloom Filters
Author :
Yan, Jeff ; Cho, Pook Leong
Author_Institution :
Newcastle University, UK
fYear :
2006
fDate :
Dec. 2006
Firstpage :
414
Lastpage :
428
Abstract :
Signature-based collaborative spam detection (SCSD) systems provide a promising solution addressing many problems facing statistical spam filters, the most widely adopted technology for detecting junk emails. In particular, some SCSD systems can identify previously unseen spam messages as such, although intuitively this would appear to be impossible. However, the SCSD approach usually relies on huge databases of email signatures, demanding lots of resource in signature lookup, storage, transmission and merging. In this paper, we report our enhancements to two representative SCSD systems. In our enhancements, signature lookups can be performed in constant time, independent of the number of signatures in the database. Space-efficient representation can significantly reduce signature database size. A simple but fast algorithm for merging different signature databases is also supported. We use the Bloom filter technique and a novel variant of this technique to achieve all this.
Keywords :
Code standards; Collaboration; Databases; Information filtering; Information filters; Internet; Merging; Performance analysis; Unsolicited electronic mail; Web server;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Security Applications Conference, 2006. ACSAC '06. 22nd Annual
Conference_Location :
Miami Beach, FL, USA
ISSN :
1063-9527
Print_ISBN :
0-7695-2716-7
Type :
conf
DOI :
10.1109/ACSAC.2006.26
Filename :
4041186
Link To Document :
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