APPARATUS AND METHOD FOR DETECTING IMAGES WITHIN SPAM

• US 20130039582A1
• Filed: 10/11/2012
• Published: 02/14/2013
• Est. Priority Date: 01/11/2007
• Status: Active Grant

• Current Assignee: Proofpoint Incorporated
• Original Assignee: Proofpoint Incorporated
• Inventors: Myers, John Gardiner, Yang, Yanyan
• Granted Patent: US 10,095,922 B2
• Time in Patent Office: Days
• US Class Current: 382/195
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

A method is described that includes comparing a characteristic of an image to stored characteristics of spam images. The method also includes generating a signature of the present image. The method further includes comparing the signature of the present image to stored signatures of spam images. The method also includes determining the spam features corresponding to the stored signatures of spam images that match the signature of the present image.

Claims

1. A computer-implemented method for determining spam features of a present image, comprising:

analyzing a the present image to determine a characteristic of the present image;

if the image has a characteristic of a first type, then executing a fuzzy feature detection algorithm to determine if the present image is a spam image; and

if the image has a characteristic of a second type, then executing a non-fuzzy feature detection algorithm to determine if the present image is a spam image.

2. The computer-implemented method as in claim 1 wherein, if the fuzzy feature detection algorithm is executed and does not detect that the image is a spam image, then executing the non-fuzzy feature detection algorithm to validate the determination of the fuzzy feature detection algorithm.

3. The computer implemented method as in claim 1 wherein the non-fuzzy feature detection algorithm computes a precise signature of at least a portion of the present image and wherein the fuzzy feature detection algorithm computes a signature of at least a portion of the present image which is relatively less precise than the signature calculated by the non-fuzzy feature detection algorithm.

4. The computer-implemented method as in claim 3 wherein the fuzzy feature detection algorithm comprises a Fuzzy80 detection algorithm and wherein the non-fuzzy feature detection algorithm comprises a GIF80 or JPEG80 detection algorithm.

5. The computer-implemented method as in claim 1 wherein the characteristic of the present image comprises whether the image is corrupted, the method further comprising:

initially executing the fuzzy feature detection algorithm to determine if the present image is a spam image if the image is not corrupted; and

initially executing the non-fuzzy feature detection algorithm to determine if the present image is a spam image if the image is corrupted.