Bayesian poisoning is a technique used by e-mail spammers to attempt to degrade the effectiveness of spam filters that rely on Bayesian spam filtering. Bayesian filtering relies on Bayesian probability to determine whether an incoming mail is spam or is not spam. The spammer hopes that the addition of random (or even carefully selected) words that are unlikely to appear in a spam message will cause the spam filter to believe the message to be legitimate—a statistical type II error.
Attributes | Values |
---|
rdf:type
| |
rdfs:label
| - Bayesian poisoning (en)
- 贝叶斯污染 (zh)
|
rdfs:comment
| - 贝叶斯污染(英語:Bayesian poisoning)是垃圾邮件制造者对抗贝叶斯垃圾邮件过滤器的一种技术。贝叶斯过滤器通过贝叶斯概率,确定一封新收到的邮件是否属于垃圾邮件。垃圾邮件制造者尝试通过随机(或专门)添加一些不太可能出现在垃圾邮件中的词语,让垃圾邮件过滤器误以为这封邮件是正常的——这是一个典型的第II型错误。 垃圾邮件制造者希望降低邮件过滤器的效率,通过在垃圾信息中夹杂一些贝叶斯数据库中的正常词汇(典型的第I型错误),因为经过训练的垃圾邮件过滤器中会有很多黑名单词汇,如果邮件中的这些黑名单词汇太多、那基本上就能判断出这是一封垃圾邮件。 (zh)
- Bayesian poisoning is a technique used by e-mail spammers to attempt to degrade the effectiveness of spam filters that rely on Bayesian spam filtering. Bayesian filtering relies on Bayesian probability to determine whether an incoming mail is spam or is not spam. The spammer hopes that the addition of random (or even carefully selected) words that are unlikely to appear in a spam message will cause the spam filter to believe the message to be legitimate—a statistical type II error. (en)
|
dcterms:subject
| |
Wikipage page ID
| |
Wikipage revision ID
| |
Link from a Wikipage to another Wikipage
| |
Link from a Wikipage to an external page
| |
sameAs
| |
dbp:wikiPageUsesTemplate
| |
has abstract
| - Bayesian poisoning is a technique used by e-mail spammers to attempt to degrade the effectiveness of spam filters that rely on Bayesian spam filtering. Bayesian filtering relies on Bayesian probability to determine whether an incoming mail is spam or is not spam. The spammer hopes that the addition of random (or even carefully selected) words that are unlikely to appear in a spam message will cause the spam filter to believe the message to be legitimate—a statistical type II error. Spammers also hope to cause the spam filter to have a higher false positive rate by turning previously innocent words into spammy words in the Bayesian database (statistical type I errors) because a user who trains their spam filter on a poisoned message will be indicating to the filter that the words added by the spammer are a good indication of spam. (en)
- 贝叶斯污染(英語:Bayesian poisoning)是垃圾邮件制造者对抗贝叶斯垃圾邮件过滤器的一种技术。贝叶斯过滤器通过贝叶斯概率,确定一封新收到的邮件是否属于垃圾邮件。垃圾邮件制造者尝试通过随机(或专门)添加一些不太可能出现在垃圾邮件中的词语,让垃圾邮件过滤器误以为这封邮件是正常的——这是一个典型的第II型错误。 垃圾邮件制造者希望降低邮件过滤器的效率,通过在垃圾信息中夹杂一些贝叶斯数据库中的正常词汇(典型的第I型错误),因为经过训练的垃圾邮件过滤器中会有很多黑名单词汇,如果邮件中的这些黑名单词汇太多、那基本上就能判断出这是一封垃圾邮件。 (zh)
|
gold:hypernym
| |
prov:wasDerivedFrom
| |
page length (characters) of wiki page
| |
foaf:isPrimaryTopicOf
| |
is Link from a Wikipage to another Wikipage
of | |
is foaf:primaryTopic
of | |