FILTERING OUTBOUND EMAIL MESSAGES USING RECIPIENT REPUTATION

• US 20090037546A1
• Filed: 07/31/2008
• Published: 02/05/2009
• Est. Priority Date: 08/02/2007
• Status: Abandoned Application

• Current Assignee: Abaca Technology Corp. (Proofpoint Incorporated)
• Original Assignee: Abaca Technology Corp. (Proofpoint Incorporated)
• Inventors: Kirsch, Steven T.
• Application Number:
  US12/183,880
• Publication Number:
  US 20090037546A1
• Time in Patent Office: Days
• US Class Current: 709/206
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]

Abstract

A method for filtering email messages by using reputations associated with recipients of the email messages to determine if senders of the email messages are spammers and correspondingly if the email messages are spam. Recipient reputations may be established based on counts of unique good senders and unique bad senders sending email messages to the recipients or by comparing sender email activity to bad recipients.

Claims

1. A method for determining whether a sender of an email message is a spammer, the method comprising:

accumulating information pertaining to recipients of email messages;

determining recipient reputations based on the accumulated information for the recipients of the email messages;

determining a sender indicator for the sender of the email message based on the recipient reputations of the recipients of the email message;

determining whether the sender is a spammer based on the sender indicator; and

filtering the email message based on the determination of whether the sender is a spammer.

2. The method of claim 1 wherein the accumulated information includes sender information pertaining to good senders and spammers.

3. The method of claim 1 wherein the accumulated information includes threshold values.

4. The method of claim 1 wherein determining recipient reputations is based on the accumulated information.

5. The method of claim 1 wherein determining the sender indicator is based on the accumulated information.

6. The method of claim 1 wherein determining a recipient reputation comprises calculating for a recipient, (a count of unique ham senders sending email messages to the recipient/a count of unique spam senders sending email messages to the recipient)/(a count of unique ham senders sending email messages to an average recipient/a count of unique spam senders sending email messages to an average recipient.

7. The method of claim 1 wherein the sender indicator is determined by multiplying the recipient reputations of unique recipients of the email message with a stored sender indicator.

8. The method of claim 1 wherein the accumulated information is updated based on an updated determination of the sender indicator.

9. The method of claim 1 further comprising compiling a set of email addresses of bad recipients.

10. The method of claim 9 wherein the set of email addresses of bad recipients is compiled using the accumulated information.

11. The method of claim 9 wherein the set of email addresses of bad recipients is compiled using the recipient reputations.

12. The method of claim 9 wherein the set of email addresses of bad recipients is compiled from a mailing list from a known spammer.

13. The method of claim 9 wherein the set of email addresses of bad recipients is compiled using at least one recipient email address collected from at least one email message sent by at least one sender regarded as a spammer.

14. The method of claim 9 wherein the accumulated information includes email addresses of the recipients in the set of email addresses of bad recipients.

15. The method of claim 9 wherein the accumulated information includes threshold values.

16. The method of claim 9 wherein the accumulated information includes, for the email messages sent to the recipients in the set of email addresses of bad recipients, a recipient email address, a sender email address, and a time the email message was sent.

17. The method of claim 9 wherein the sender indicator is determined based on the email messages sent to the recipients in the set of email addresses of bad recipients.

18. The method of claim 9 wherein the sender indicator is determined based on a first count of unique recipients in the set of email addresses of bad recipients to whom the sender has sent the email messages over a given interval of time.

19. The method of claim 9 wherein the sender indicator is determined based on a second count of the email messages sent from the sender, over a given interval of time, to the recipients in the set of email addresses of bad recipients.

20. A method for determining whether a sender of an email message is a spammer, the method comprising:

compiling a list of bad recipients, the list of the bad recipients comprising email addresses of recipients considered likely to receive spam email messages;

storing sender activity data pertaining to email messages sent to the bad recipients;

accumulating a first set of counts of the email messages sent by the sender to the bad recipients over a given time interval using the sender activity data;

accumulating a second set of counts of unique bad recipients to whom the sender has sent the email messages over the given time interval using the sender activity data;

making a first determination whether the sender is a spammer by comparing the first set of counts to a first threshold;

making a second determination whether the sender is a spammer by comparing the second set of counts to a second threshold;

filtering the email message based on at least one of the first determination and the second determination of whether the sender is a spammer; and

updating the list of the bad recipients based on at least one of the first determination and the second determination.

21. A method for determining whether a sender of an email message is a spammer, the method comprising:

compiling a list of bad recipients, the list of the bad recipients comprising email addresses of recipients considered likely to receive spam email messages;

storing sender activity data pertaining to email messages sent to the bad recipients;

accumulating counts of the email messages sent by the sender to the bad recipients over a given time interval using the sender activity data;

determining whether the sender is a spammer by comparing the counts to a threshold;

filtering the email message based on the determination of whether the sender is a spammer; and

updating the list of the bad recipients based on the determination of whether the sender is a spammer.

22. A method for determining whether a sender of an email message is a spammer, the method comprising:

compiling a list of bad recipients, the list of the bad recipients comprising email addresses of recipients considered likely to receive spam email messages;

storing sender activity data pertaining to email messages sent to the bad recipients;

accumulating counts of unique bad recipients to whom the sender has sent the email messages over a given time interval using the sender activity data;

determining whether the sender is a spammer by comparing the counts to a threshold;

filtering the email message based on the determination of whether the sender is a spammer; and

updating the list of the bad recipients based on the determination of whether the sender is a spammer.