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Which of the following fiterling solutions would be the most effective means to stop a valid, variable length email message contain a weighted spam keyword from being identified as spam?
Bayesian (statistical)
Signature-based
Heuristic (rule-based)
Pattern matching
Bayesian filtering applies statistical modeling to messages by performing a frequency analysis on each word within the message and then evaluating the message as a whole. Therefore, it can ignore a suspicious keyword if the entire message is within normal bounds. Heuristic filtering is less effective, since new exception rules may need to be defined when a valid message is labeled as spam. Signature-based filtering is useless against variable-length messages, because the calculated message-digest algorithm 5 (MD5) hash changes all the time. Finally, pattern matching is actually a degraded rule-based technique, where the rules operate at the word level using wildcards, and not at higher levels.
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