WHITE List vs BLACK List E-mail Filtering
(Or "Why Spam Filters Using BLACK Lists Fail")

FILTERING RULES:

IF WHITE list entry matches e-mail field content, THEN mail is WANTED; ELSE it's UNWANTED
IF BLACK list entry matches e-mail field content, THEN mail is UNWANTED; ELSE it's WANTED

FILTERING RESULTS:

For any given set of of e-mails, WHITE list filtering and BLACK list filtering of field content will produce exactly identical results IF AND ONLY IF the Black list contains all possible field content entries that are NOT contained in the WHITE list. See example

FILTERING STRATEGY ANALYSIS

Combinatorial theory teaches that a field 'M' characters in length composed of 'N' unique characters has 'M raised to the Nth power' (= M^N) possible different combinations. See proof

Assume filtering is based on e-mails' "FROM"-field - which contains the sender's e-mail address. An e-mail address is expressed as a unique combination of 39 different characters: 'a' thru 'z', '0' thru '9', '@', underscore, period.

An 18-character e-mail "FROM"-field (e.g.; 'rasinralph@aol.com') has 39¹⁸ = 4.36 x 10²⁸ =
4.36 x 10,000,000,000,000,000,000,000,000,000 possible combinations.

If a WHITE list contains 1000 e-mail address entries, a BLACK list that produces exactly the same filtering results must contain (4.36 x 10,000,000,000,000,000,000,000,000,000) -1000 entries!

If the time required for each compare of a list entry with the e-mail field is 1 millisecond, then:
o Time required to compare of all WHITE list entries = 1 SECOND
o Time required to compare of all BLACK list entries = 1.38 x 10¹⁸ YEARS
*** NOTE: The estimated age of the Earth is 4.5 billion (4.5 x 10⁹) years ***

CONCLUSION: USE ONLY WHITE LISTS, BECAUSE:

1. Increases in filtered-field character count and permitted unique character have no effect on the number of WHITE list entries but drastically increase the number of required BLACK list entries. A 30-character "SUBJECT" field composed from 127 allowable characters has 127³⁰ possible combinations ( = 1.3 x 10⁶³ )
2. A WHITE list filters 100% correctly. A BLACK list filters 99.9999999999% incorrectly.
3. WHITE lists are far less labor-intensive to create and maintain than BLACK lists.
4. WHITE lists are far more likely to be complete than BLACK lists.
5. WHITE lists are far more filtering time-efficient and cost-effective than BLACK lists.