Abstract: Disclosed herein is a system and method for identifying a spam email message. To identify a spam message a similarity measurement hash and a sender hash is generated for each email message. Two or more previously received email messages are compared with an incoming email message. The incoming email message is identified as a spam message when the similarity measurement hash between incoming message and one of the received messages matches and the corresponding sender hash does not match. The system may integrate with other email servers through a DNS to identify spam emails across different organizations and locations. The system and method may further apply rules to particular match to whitelist a potential spam email.

Abstract: Disclosed herein is a system and method for identifying a spam email message. To identify a spam message a similarity measurement hash and a sender hash is generated for each email message. Two or more previously received email messages are compared with an incoming email message. The incoming email message is identified as a spam message when the similarity measurement hash between incoming message and one of the received messages matches and the corresponding sender hash does not match. The system may integrate with other email servers through a DNS to identify spam emails across different organizations and locations. The system and method may further apply rules to particular match to whitelist a potential spam email.

Abstract: Disclosed herein is a system and method for identifying a spam email message. To identify a spam message a similarity measurement hash and a sender hash is generated for each email message. Two or more previously received email messages are compared with an incoming email message. The incoming email message is identified as a spam message when the similarity measurement hash between incoming message and one of the received messages matches and the corresponding sender hash does not match. The system may integrate with other email servers through a DNS to identify spam emails across different organizations and locations. The system and method may further apply rules to particular match to whitelist a potential spam email.

Abstract: Disclosed herein is a system and method for identifying a spam email message. To identify a spam message a similarity measurement hash and a sender hash is generated for each email message. Two or more previously received email messages are compared with an incoming email message. The incoming email message is identified as a spam message when the similarity measurement hash between incoming message and one of the received messages matches and the corresponding sender hash does not match. The system may integrate with other email servers through a DNS to identify spam emails across different organizations and locations. The system and method may further apply rules to particular match to whitelist a potential spam email.