spam Policies CSG – January 2003 Dan Oberst – Princeton University

spam Filter Survey Survey Cornell University Harvard (Central Admin Only) Penn State University Princeton University University of Buffalo University of Calif. Office of Pres. University of Minnesota University of Washington University of Wisconsin

Princeton Experience Experience  Filtering using spam Assassin  ALL messages >300K tagged  Users “opt in” and choose threshold Messages moved to spam folder Messages moved to spam folder  87,000 messages/day (since 11/1)  50% meet default threshold  Users can post/local process (procmail, etc.)  ~1,250 users have opted in (~10%)

Horsepower  Original (current) server SUN 280R SUN 280R 4 GB memory4 GB memory 4x36 (external SCSI); 2x9 GB (internal) disks4x36 (external SCSI); 2x9 GB (internal) disks mirrored ~75 GB mirrored ~75 GB Adding spindles improved performanceAdding spindles improved performance External postoffice External postoffice Runs Norton Anti-virus scanning (opt-out) Runs Norton Anti-virus scanning (opt-out)

Horsepower (future)  Part of plan to provide redundant servers  2 x Sun V480 (4 processors) 8 GB memory 8 GB memory 2x36 GB (internal);12x18GB (SCSI) disks raw 2x36 GB (internal);12x18GB (SCSI) disks raw mirrored ~135GBmirrored ~135GB Lots of spindles for performance Lots of spindles for performance  spam filtering, Norton A/V  Capacity for user whitelists, growth, etc.

Princeton  Add user whitelists  Consider border blacklisting/blocking  Commercial software options? Improved performance Improved performance Better scoring Better scoring  Integrate with client (e.g. OS/X) software Peer-to-peer options Peer-to-peer options