After four months of development DSPAM v3.2 has been released, bringing many new enhancements and filtering technologies…
These include distributed computing support, implementation of Bill Yerazunis’ Sparse Binary Polynomial Hashing algorithm (from CRM114), and v1.2 of Bayesian Noise Reduction. Other enhancements include SQLite support and many significant performance enhancements for PostgreSQL. DSPAM’s official release is next week, but you can download the preview release now. Users of the project have also contributed towards creating a new logo for this release.”
DSPAM Introduction:
DSPAM (as in De-Spam) is an extremely scalable, open-source statistical anti-spam filter. While most commercial solutions only claim a mere 95% accuracy (1 error in 20), a majority of DSPAM users frequently see around 99.95% (1 error in 2000) and can sometimes reach peaks as high as 99.991% (2 errors in 22,786). DSPAM presently functions as both a server-side agent for UNIX email servers and a developer’s library for mail clients, other anti-spam tools, and similar projects requiring drop-in spam filtering. DSPAM has been implemented on many large and small scale systems with the largest being reported at about 350,000 mailboxes.
DSPAM is a dedicated statistical filter and in being such provides higher accuracy levels than commercial “hodge-podge” solutions, and with minimal resources. DSPAM has managed to achieve nearly equal levels of accuracy with present-day Markovian-based filters and other types of filters that employ large feature sets with the added benefit of using a significantly fewer amount of resources. DSPAM’s best recorded levels of accuracy have included 99.991% by one avid user (2 errors in 22,786) and 99.987% by the author(1 error in 7000) , which is ten times more accurate than a human being! ( According to a study by Bill Yerazunis of CRM114. )
DSPAM Features:
Source
Slashdot
Download and more
DSPAM – http://www.nuclearelephant.com/projects/dspam/
Whats new in 3.2?
No tags