ANTI-SPOOFING SYSTEM AND METHODS USEFUL IN CONJUNCTION THEREWITH

• US 20180034852A1
• Filed: 11/24/2015
• Published: 02/01/2018
• Est. Priority Date: 11/26/2014
• Status: Abandoned Application

• Current Assignee: IsItYou Ltd.
• Original Assignee: IsItYou Ltd.
• Inventors: GOLDENBERG, Shmuel
• Application Number:
  US15/531,229
• Publication Number:
  US 20180034852A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/2411 based on the proximity to a decision surface, e.g. support vector machines
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06V 10/42 Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
• CPC Class Codes: G06V 10/48 by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
• CPC Class Codes: G06V 10/54 relating to texture
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 40/40 Spoof detection, e.g. liveness detection
• CPC Class Codes: H04L 63/0861 using biometrical features, e.g. fingerprint, retina-scan cryptographic mechanisms or cryptographic arrangements for entity authentication using biological data H04L9/3231
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1483 service impersonation, e.g. phishing, pharming or web spoofing detection of rogue wireless access points H04W12/12

Abstract

An anti-spoofing system operative for repulsing spoofing attacks in which an impostor presents a spoofed image of a registered end user, the system comprising a plurality of spoof artifact identifiers including a processor configured for identifying a respective plurality of spoofed image artifacts in each of a stream of incoming images and a decision maker including a processor configured to determine an individual image in the stream is authentic only if a function of artifacts identified therein is less than a threshold criterion.

Claims

1. An anti-spoofing system operative for repulsing spoofing attacks in which an impostor presents a spoofed image of a registered end user, the system comprising:

a plurality of spoof artifacts identifiers including a processor configured for identifying a respective plurality of spoofed image artifacts in each of a stream of incoming images; and

a decision maker configured to determine an individual image in the stream is authentic only if a function of artifacts identified therein is less than a threshold criterion.

2. A system according to any preceding claim wherein the function of artifacts comprises the number of artifacts identified.

3. A system according to claim 1 or 2 wherein the artifact identifier includes a heuristic gradient detector operative to detect at least one heuristic typical of spoof attempts.

4. A system according to any preceding claim wherein the artifact identifier includes proximity detection.

5. A system according to any preceding claim wherein the artifact identifier includes a lumiosity analyzer configured to map image luminosity distribution and to identify an artifact based on previously learned statistics regarding image luminosity distribution.

6. A system according to any preceding claim wherein the artifact identifier includes a Learning Block operative to learn a pattern of spoof attempts and capable to predict the next attempt type based on previously learned statistics.

7. A system according to any preceding claim wherein the artifact identifier includes an oscillating pattern detector operative to map moiré

patterns characteristic of video based spoofing attempts.

8. A system according to claim 2 wherein the threshold criterion stipulates that an individual image in the stream is authentic only if no (zero) artifacts are identified therein.

9. A system according to any preceding claim wherein at least one spoof artifact identifier is configured to detect spoofed image artifacts present in plural images within a repository, in computer storage, of spoofed facial images.

14. A system according to claim 9 wherein at least some of said images are generated using a mobile device.

15. A system according to claim 9 wherein at least some of said images are generated in the wild.

17. A system according to claim 7 wherein the oscillating pattern detector is configured to:

Identify smooth image areas which contain potential oscillating-like patterns and extract image statistics therefrom;

Form corresponding feature vectors from the image statistics; and

detect oscillating patterns by classifying feature vectors as real or attack feature vectors.

18. A system according to claim 17 wherein said oscillating patterns are detected using Lagrangian Support Vector Machines (LSVMs).

10. A repository, in computer storage, of spoofed facial images generated using a mobile device to image a spoof of a human face rather than the human face itself.

11. A repository according to claim 10 which also includes facial images which are not spoofs.

12. A repository according to claim 10 which also includes facial images which are not generated using a mobile device.

13. A repository, in computer storage, of spoofed facial images generated in the wild.

16. An anti-spoofing method operative for repulsing spoofing attacks in which an impostor presents a spoofed image of a registered end user, the method comprising:

Providing a plurality of spoof artifact identifiers including a processor configured for identifying a respective plurality of spoofed image artifacts in each of a stream of incoming images; and

Determining an individual image in the stream is authentic only if a function of artifacts identified therein is less than a threshold criterion.

19. A computer program product, comprising a non-transitory tangible computer readable medium having computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method for anti-spoofing operative for repulsing spoofing attacks in which an impostor presents a spoofed image of a registered end user, the method comprising:

Providing a plurality of spoof artifact identifiers including a processor configured for identifying a respective plurality of spoofed image artifacts in each of a stream of incoming images; and

Determining an individual image in the stream is authentic only if a function of artifacts identified therein is less than a threshold criterion.