Abstract: Techniques to select and prioritize the application of spam filtering rules in a way that reduces processing time may include receiving an email message for a recipient at a spam filter and extracting email characteristics from the message. Global filtering rule statistics and a profile for the recipient may be retrieved. The technique may include selecting a subset of rules from a set of filtering rules according to the email characteristics, the global filtering rule statistics, and/or the recipient characteristics. The subset of rules may be prioritized and applied to the message from highest priority to lowest until a determination of whether the message is spam is reached. Other embodiments are described and claimed.

Abstract: Technologies are described related to third party email signature generation and authentication. A DKIM signature may be stamped in a way such that the “From” address is encoded in the selector. The domain may be extracted from the DKIM signature based upon being from a known sender in the d=field, which signs on behalf of another domain. The reconstructed domain may be aligned from the selector against the actual domain in the “From” address to pass DMARC.

Abstract: A messaging application filters electronic messages based on domain attributes without a reputation. A message with a uniform resource identifier (URI) is received and determined to not be included within a trusted or a block list. A total score is computed from weighted scores assigned to factors associated with the message. The message is evaluated for an unsolicited message determination by comparing the total score against a predetermined threshold.

Abstract: Techniques to select and prioritize the application of spam filtering rules in a way that reduces processing time may include receiving an email message for a recipient at a spam filter and extracting email characteristics from the message. Global filtering rule statistics and a profile for the recipient may be retrieved. The technique may include selecting a subset of rules from a set of filtering rules according to the email characteristics, the global filtering rule statistics, and/or the recipient characteristics. The subset of rules may be prioritized and applied to the message from highest priority to lowest until a determination of whether the message is spam is reached. Other embodiments are described and claimed.

Abstract: Techniques to select and prioritize the application of spam filtering rules in a way that reduces processing time may include receiving an email message for a recipient at a spam filter and extracting email characteristics from the message. Global filtering rule statistics and a profile for the recipient may be retrieved. The technique may include selecting a subset of rules from a set of filtering rules according to the email characteristics, the global filtering rule statistics, and/or the recipient characteristics. The subset of rules may be prioritized and applied to the message from highest priority to lowest until a determination of whether the message is spam is reached. Other embodiments are described and claimed.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: Technologies are described related to third party email signature generation and authentication. A DKIM signature may be stamped in a way such that the “From” address is encoded in the selector. The domain may be extracted from the DKIM signature based upon being from a known sender in the d= field, which signs on behalf of another domain. The reconstructed domain may be aligned from the selector against the actual domain in the “From” address to pass DMARC.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: Techniques to detect spam using language and a country of origin of an e-mail may include receiving an e-mail message for a recipient, detecting a country of origin for the e-mail message and detecting a language of the e-mail message. A technique may further include determining a country frequency with which the recipient communicates with the country of origin by e-mail, and a language frequency with which the recipient communicates in the language by e-mail. A technique may assign a first score to the message according to the country frequency, and a second score to the message according to the language frequency. The scores may used to determine whether the e-mail message is spam. Other embodiments are described and claimed.

Abstract: A messaging application filters electronic messages based on domain attributes without a reputation. A message with a uniform resource identifier (URI) is received and determined to not be included within a trusted or a block list. A total score is computed from weighted scores assigned to factors associated with the message. The message is evaluated for an unsolicited message determination by comparing the total score against a predetermined threshold.

Abstract: A messaging application filters electronic messages based on domain attributes without a reputation. A message with a uniform resource identifier (URI) is received and determined to not be included within a trusted or a block list. A total score is computed from weighted scores assigned to factors associated with the message. The message is evaluated for an unsolicited message determination by comparing the total score against a predetermined threshold.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: Content is received and compared against rules for identifying a type of content. Each rule has both segmented and unsegmented patterns. The content is matched against the patterns and assigned a confidence score that is higher if the content matches a segmented pattern and lower if the content matches an unsegmented pattern.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: A messaging application filters electronic messages based on domain attributes without a reputation. A message with a uniform resource identifier (URI) is received and determined to not be included within a trusted or a block list. A total score is computed from weighted scores assigned to factors associated with the message. The message is evaluated for an unsolicited message determination by comparing the total score against a predetermined threshold.

Abstract: Techniques to transform regular expressions are described. An apparatus may comprise a processor circuit and a key terms identifying module operative on the processor circuit to generate a set of one or more regular expression key terms from enabled features of a regular expression based on a set of configuration parameters, and filter one or more electronic messages using the set of regular expression key terms. Other embodiments are described and claimed.

Abstract: Techniques to select and prioritize the application of spam filtering rules in a way that reduces processing time may include receiving an email message for a recipient at a spam filter and extracting email characteristics from the message. Global filtering rule statistics and a profile for the recipient may be retrieved. The technique may include selecting a subset of rules from a set of filtering rules according to the email characteristics, the global filtering rule statistics, and/or the recipient characteristics. The subset of rules may be prioritized and applied to the message from highest priority to lowest until a determination of whether the message is spam is reached. Other embodiments are described and claimed.

Abstract: Techniques to detect spam using language and a country of origin of an e-mail may include receiving an e-mail message for a recipient, detecting a country of origin for the e-mail message and detecting a language of the e-mail message. A technique may further include determining a country frequency with which the recipient communicates with the country of origin by e-mail, and a language frequency with which the recipient communicates in the language by e-mail. A technique may assign a first score to the message according to the country frequency, and a second score to the message according to the language frequency. The scores may used to determine whether the e-mail message is spam. Other embodiments are described and claimed.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.