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1、Which of the following antispam filtering techniques would BEST prevent a valid, variable-length e-mail message containing a heavily weighted spam keyword from being labeled as spam?
A、Heuristic (rule-based)
B、Signature-based
C、Pattern matching
D、Bayesian (statistical)
ANSWER:D
NOTE: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 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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