IP Library Granted Patent US 10,108,918
Granted Patent B2
US 10,108,918 · App. 14/478,714 · Granted Oct 23, 2018

Method and system for inferring risk of data leakage from third-party tags

Inventors: Vivek Palan (San Francisco, CA); Paul Owen (Bend, OR); Frank Ledo (Berkeley, CA); Ben Jolitz (Los Gatos, CA)
Assignee: Acxiom Corporation
G06Q10/0635G06F21/51G06F21/577G06Q30/02H04L63/1433H04L63/1466G06F2221/2119
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Quick Facts
Patent No.
US 10,108,918
App. No.
14/478,714
Granted
Oct 23, 2018
Kind
B2
Abstract

A method and system for assessing the data leakage threat associated with third-party tags on a particular website, such as a content publisher site, is assessed by mimicking a standard web browser. Each third-party tag on the site is identified and investigated in a hierarchical manner, and a data leakage threat score is assigned to each third-party tag based on certain attributes associated with the tag and the resource linked by the third-party tag. A cumulative data leakage threat score is then calculated to determine if the site is a data leakage threat, such as a threat for misuse of a consumer's data.

Claims (45)

1. A computer-implemented method for identifying data leakage across an Internet connection, comprising the steps of:

a. accessing via threat analysis software hosted on at least one marketing services provider (MSP) server an Internet website hosted at a publisher server, wherein the MSP server is configured to mimic a standard web browser such that it appears from the Internet website as if the MSP server is a consumer using the standard web browser to access the Internet website but wherein the MSP server is actually configured to analyze the Internet website for data leakage;

b. searching the Internet website to identify any third-party tags on the Internet website;

c. determining whether any of the third-party tags forward requests to subsequent third-party tags, thereby allowing the subsequent third-party tags to piggyback through inspection of the Internet website at the time the Internet website is loaded;

d. if it is determined that subsequent third-party tags are piggybacking on the Internet website, dynamically calculating an individual threat score associated with each third-party tag found on the Internet website based on use by each third-party tag of any personal information associated with an individual accessing the Internet website;

e. if individual threat scores are calculated, calculating a cumulative threat score associated with the Internet website based on the individual threat scores; and

f. if a cumulative threat score is calculated, then determining whether the cumulative threat score is above a threshold threat score, and if so identifying the Internet website as a data leakage threat.

2. The computer-implemented method of claim 1 , wherein the Internet website is associated with an Internet domain, and further comprising the steps of:

a. searching for the Internet domain in a table of known data leaker Internet domains;

b. identifying the Internet website as a data leakage threat if the Internet domain associated with the Internet website is found in the table of known data leaker Internet domains; and

c. updating the table of known data leakers if the Internet domain is shared with other websites.

3. The computer-implemented method of claim 2 , wherein the step of calculating individual threat scores comprises the step of determining whether an Internet-based resource associated with each third-party tag exhibits any of a plurality of attributes, wherein each attribute is associated with a data leakage threat.

4. The computer-implemented method of claim 3 , wherein each attribute is associated with a numerical threat score.

5. The computer-implemented method of claim 4 , wherein the individual threat score is calculated as a sum of the threat scores associated with each attribute associated with each third-party tag.

6. The computer-implemented method of claim 5 , wherein the cumulative threat score is calculated as a sum of the individual threat scores.

7. The computer-implemented method of claim 1 , wherein the threshold is a numerical score that is at least as high as an identified percentage of a plurality of reference cumulative threat scores.

8. The computer-implemented method of claim 1 , wherein a second MSP server geographically remote from the MSP server, but connected by the Internet, repeats steps (a) and (b).

9. A computer program product for assessing a risk associated with data leakage on the Internet, the computer program product being stored on a non-transitory tangible computer-readable medium and comprising instructions that, when executed, cause a computer system to:

a. access via threat analysis software hosted on at least one marketing services provider (MSP) server an Internet website hosted at a publisher server, wherein the analysis software mimics a standard web browser such that the Internet website appears to be accessed in the same manner as it would be accessed by a standard web browser but wherein the MSP server is actually configured to analyze the Internet website for data leakage;

b. search the Internet website to identify any third-party tag piggybacking, wherein identifying third-party tag piggybacking comprises determining whether any third-party tags forward requests to subsequent third-party tags;

c. dynamically calculate an individual threat score associated with each instance of third-party tag piggybacking found on the Internet website based on any use by each third-party tag of personal information associated with an individual accessing the Internet website;

d. calculate a cumulative threat score associated with the Internet website based on each individual threat score; and

e. if the cumulative threat score is above a threshold threat score, return an indicator that the Internet website is a data leakage threat.

10. The computer program product of claim 9 , further comprising instructions that, when executed, cause a computer system to search an Internet domain associated with the Internet website in a table of known data leaker Internet domains, and identify the Internet website as a data leakage threat if the Internet domain associated with the Internet website is found in the table of known data leaker domains.

11. The computer program product of claim 10 , further comprising instructions that, when executed, cause a computer system to determine whether a resource associated with each third-party tag exhibits any of a plurality of attributes, wherein each attribute is associated with an Internet-based data leakage threat.

12. The computer program product of claim 11 , wherein each attribute is associated with a numerical threat score.

13. The computer program product of claim 12 , further comprising instructions that, when executed, cause a computer system to calculate the individual threat score as a sum of the threat scores associated with each attribute associated with each third-party tag.

14. The computer program product of claim 13 , further comprising instructions that, when executed, cause a computer system to calculate the cumulative threat score as a sum of the individual threat scores.

15. The computer program product of claim 9 , wherein the threshold is a threat score that is at least as high as a set percent of a database of dynamically calculated reference cumulative threat scores.

16. A system for determining a threat of data leakage for an Internet website, comprising:

a. a marketing services provider (MSP) server configured to access the Internet website in a manner that mimics a standard web browser such that it appears to the Internet website that the MSP server is a consumer using the standard browser but wherein the MSP server is actually configured to analyze the Internet website to identify and investigate any third-party tag piggybacking found on the Internet website, wherein third-party tag piggybacking comprises a third-party tag forwarding requests to at least one subsequent third-party tag;

b. a leaker table stored in a non-transitory computer-readable medium in communication with the MSP server, wherein the leaker table comprises a plurality of Internet domains known to be data leakers; and

c. an attribute table stored in a non-transitory computer-readable medium in communication with the MSP server, wherein the attribute table comprises a plurality of attributes for an Internet domain associated with a threat of Internet-based data leakage based on use by any third-party tag of personal information associated with an individual.

17. The system for determining a threat of data leakage across the Internet for a website of claim 16 , wherein the attribute table further comprises, for each attribute, a numerical threat value associated with the attribute.

18. The system for determining a threat of data leakage across the Internet for a website of claim 17 , wherein the MSP server is further configured to identify each of the attributes from the attribute table associated with each third-party tag found on the Internet website.

19. The system for determining a threat of data leakage across the Internet for a website of claim 18 , wherein the MSP server is further configured to dynamically calculate an individual threat score for each third-party tag by summing the numerical threat value for each attribute associated with the third-party tag.

20. The system for determining a threat of data leakage across the Internet for a website of claim 19 , wherein the MSP server is further configured to calculate a cumulative threat score by summing the individual threat scores associated with each of the third-party tags on the Internet website.

21. The system for determining a threat of data leakage across the Internet for an Internet website of claim 20 , wherein the MSP server is further configured to compare the cumulative threat score to a threshold threat score, and return a threat result if the cumulative threat score is at least as high as the threshold score.

22. The system for determining a threat of data leakage across the Internet for a website of claim 16 , further comprising at least one additional MSP server located in a geographically remote location from the MSP server and connected via the Internet and configured to access the Internet website in the manner of a standard web browser but configured to analyze the Internet website to identify and investigate any third-party tag piggybacking found on the Internet website.

23. The method of claim 1 , wherein the step of dynamically calculating the individual threat scores associated with each third-party tag comprises a Bayesian inference analysis of attributes associated with a plurality of Internet domains, such that Internet domains with similar attributes to known data leakage Internet domains receive higher threat scores and domains with similar attributes to known non-data leakage Internet domains receive lower threat scores.

24. The method of claim 1 , wherein the step of dynamically calculating the individual threat scores associated with each third-party tag comprises the step of considering loose conditions for a set of threats and adjusting a magnitude of the threat scores through an averaged centroid based off of a frequency and aggregate scores relative to each threat.

25. The method of claim 24 , wherein the step of dynamically calculating the individual threat scores comprises the step of calculating an ideal median threat percentage based upon a distribution of threats in all Internet websites analyzed.

26. The method of claim 25 , wherein an ideal median threat percentage is calculated based upon the distribution of threats in all Internet websites analyzed, and is defined as occurring half the time with a set threat score and then scaling the threat scores of other threats around the ideal medial threat percentage.

27. The method of claim 26 , further comprising the calculation of a highest score by doubling a default score for a threat that occurs half of the time.

28. The method of claim 25 , wherein more common-appearing threats are de-emphasized in the step of dynamically calculating individual threat scores by creating an inverse relationship between a percent of time a threat is seen against an ideal percentage of the most common threat.

Assignments (3)
NUNC PRO TUNC ASSIGNMENT Recorded Jan 2, 2019
From: ACXIOM LLC
To: LIVERAMP, INC.
Reel/Frame 047999/0796 →
CHANGE OF NAME Recorded Oct 2, 2018
From: ACXIOM CORPORATION
To: ACXIOM LLC
Reel/Frame 047185/0083 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 5, 2014
From: PALAN, VIVEK; OWEN, PAUL; LEDO, FRANK; JOLITZ, BEN
To: ACXIOM CORPORATION
Reel/Frame 033680/0695 →
Continuity (2)
Provisional Application 61879909 · Sep 19, 2013
Related Publication 20150082426A1 · Mar 19, 2015