Source: http://www.google.com/patents/US8006314?dq=7,669,134
Timestamp: 2017-11-19 22:42:27
Document Index: 699201464

Matched Legal Cases: ['Application No. 02725522', 'Application No. 02752347', 'Application No. 02756525', 'Application No. 02782170', 'Application No. 04706547', 'Application No. 05778109']

Patent US8006314 - System for identifying content of digital data - Google Patents
A system for identifying a work represented by digital data. This system detects events in data of the content of an unknown work and measures a metric between the events. The system then compares the detected events and metrics from an unknown work with the events and metrics of a known work. If the...http://www.google.com/patents/US8006314?utm_source=gb-gplus-sharePatent US8006314 - System for identifying content of digital data
Publication number US8006314 B2
Application number US 11/829,662
Also published as US8112818, US8732858, US9268921, US9785757, US20090030651, US20090031326, US20120124679, US20140215643, US20160132664, WO2009017710A1
Publication number 11829662, 829662, US 8006314 B2, US 8006314B2, US-B2-8006314, US8006314 B2, US8006314B2
Inventors Erling Wold
Patent Citations (199), Non-Patent Citations (149), Referenced by (72), Classifications (17), Legal Events (4)
US 8006314 B2
1. A method for identifying a work in a digital processing system comprising:
selecting, by a processor, a portion of data of an unknown work;
detecting each event in said portion of data of said unknown work;
determining a metric between each successive event in said portion of data in said unknown work;
generating a list of metrics between said events for said unknown work;
comparing said list of metrics for said unknown work to a list of metrics for a known work, wherein the comparing comprises
receiving said list of metrics of said unknown work and said list of metrics of said known work,
determining a number of events in said list of metrics for said unknown work that match events in said list of metrics for said known work by
receiving said list of metrics for said unknown work starting at the Mth element,
receiving said list of metrics of said known work starting at the Nth element,
generating a list of associated pairs wherein each M+X element of said list of metrics for said unknown work is paired with the N+X element of said list of metrics for said known work,
computing a regression line through said associated pair in said list of associated pairs,
determining a weighted error from said computation of said regression line,
comparing said weighted error to a weighted error threshold, and
determining a match between said lists responsive to said weighted error being less than said weighted error threshold,
determining whether said number at least equals a threshold, and
returning a match responsive to said number being at least equal to said threshold; and
determining said unknown work is a copy of said known work responsive to a match between said list of metrics of said unknown work and said list of metrics for said known work.
comparing said list of metrics of said unknown work to a plurality of lists of metrics wherein each list of metrics is for a known work responsive to a determination that said list of metrics of said unknown work did not match said list of metrics of said known work;
determining said unknown work is a copy of one of said known works responsive to a match of said list of metrics of said unknown work and said one of said plurality of lists that represents said one of said known works.
generating a group of said plurality of lists of metrics from known works that are likely to match said unknown work.
receiving a segment of data of said unknown work; and
selecting said portion of data from said segment of data received.
5. The method of claim 4 wherein said step of receiving said segment of data comprises:
reading said segment of data from memory.
6. The method of claim 4 wherein said step of receiving said segment of data comprises:
receiving packets over a network wherein each packet includes a portion of said segment of data;
extracting said portion of said segment of data from each of said packets; and
reassembling said segment of data from said packets.
7. The method of claim 4 wherein said step of receiving said segment of data comprises:
reading said segment of data from a media storing said segment of data.
determining whether said unknown work is an authorized copy of said known work responsive to a determination that said unknown work is a copy of said known work.
performing a business rule in response to a determination that said unknown work is an unauthorized copy.
reporting said unknown work is an unauthorized copy responsive to a determination that said unknown work is an unauthorized copy of said known work.
performing a secondary test responsive to a determination that said list of said unknown work does match said list of said known work.
12. The method of claim 1 further comprising;
performing a secondary test responsive to a determination that said comparison between said list of said unknown work and said list of said known work are inconclusive.
performing a secondary test to verify an identity of said unknown work responsive to a determination that said list of said unknown work matches said known work.
14. The method of claim 1 wherein determining said number comprises:
aligning an Mth element of said list of metrics of said unknown work with an Nth element of said list of metrics for said known work;
performing a first comparison of said lists starting from said Mth element in said list of metrics for said unknown list and said Nth element in said list of metrics for said known work;
determining whether said lists from said Mth element and said Nth element match; and
determining a match responsive to a determination said lists match.
recursively determining whether elements of said list of metrics for said unknown work match elements of said list of metrics for said known work.
16. The method of claim 1 wherein said step for determining a match between said list of metrics for said unknown work and said list of metrics for said known work further comprises:
determining a match when a number of hits surpasses a threshold.
17. The method of claim 1 wherein said step for determining a match between said list of metrics for said unknown work and said list of metrics for said known work further comprises:
determining there is no match responsive to a number of misses being greater than a second threshold.
18. The method of claim 1 wherein said step for determining a match between said list of metrics for said unknown work and said list of metrics for said known work further comprises:
19. The method of claim 1 wherein said step for determining a match between said list of metrics for said unknown work and said list of metrics for said known work further comprises:
determining a match between said lists responsive to said regression error being less than said regression error threshold.
20. A method for identifying a work in a digital processing system comprising:
comparing said list of metrics for said unknown work to a list of metrics for a known work, wherein the comparing comprises:
determining a number of events in said list of metrics for said unknown work that match events in said list of metrics for said known work, wherein determining the number of events comprises:
determining a miss ratio from said computation of said regression line,
comparing said miss ratio to a miss ratio threshold, and
determining a match between said lists responsive to said miss ratio being less than said miss ratio threshold,
21. A method for identifying a work in a digital processing system comprising:
determining a match between said lists responsive to said weighted miss ratio being less than said weighted miss ratio threshold,
22. A non-transitory computer readable storage medium that provides instructions for identifying a work in a digital processing system, the instructions when executed by a processing unit, cause the processing unit to:
detect each event in said portion of data of said unknown work;
determine a metric between each successive event in said portion of data in said unknown work;
generate a list of metrics between said events for said unknown work;
compare said list of metrics for said unknown work to a list of metrics for a known work, wherein to compare said list of metrics for said unknown work to a list of metrics for a known work comprises
determine said unknown work is a copy of said known work responsive to a match between said list of metrics of said unknown work and said list of metrics for said known work.
23. The non-transitory computer readable storage medium of claim 22, wherein said instructions further cause the processing unit to:
compare said list of metrics of said unknown work to a plurality of lists of metrics wherein each list of metrics is for a known work responsive to a determination that said list of metrics of said unknown work did not match said list of metrics of said known work; and
determine said unknown work is a copy of one of said known works responsive to a match of said list of metrics of said unknown work and said one of said plurality of lists that represents said one of said known works.
24. The non-transitory computer readable storage medium of claim 22, wherein said instructions cause the processing unit to determine said number by:
25. The non-transitory computer readable storage medium of claim 22, wherein said instructions further cause the processing unit to:
recursively determine whether elements of said list of metrics for said unknown work match elements of said list of metrics for said known work.
26. A non-transitory computer readable storage medium that provides instructions for identifying a work in a digital processing system, the instructions when executed by a processing unit, cause the processing unit to:
determining a number of events in said list of metrics for said unknown work that match events in said list of metrics for said known work, wherein determining the number of events comprises
27. The non-transitory computer readable storage medium of claim 26, wherein said instructions further cause the processing unit to:
28. The non-transitory computer readable storage medium of claim 26, wherein said instructions cause the processing unit to determine said number by:
29. The non-transitory computer readable storage medium of claim 26, wherein said instructions further cause the processing unit to:
30. A non-transitory computer readable storage medium that provides instructions for identifying a work in a digital processing system, the instructions when executed by a processing unit, cause the processing unit to:
determining a weighted miss ratio from said computation of said regression line,
comparing said weighted miss ratio to a weighted miss ratio threshold, and
31. The non-transitory computer readable storage medium of claim 30, wherein said instructions further cause the processing unit to:
32. The non-transitory computer readable storage medium of claim 30, wherein said instructions cause the processing unit to determine said number by:
33. The non-transitory computer readable storage medium of claim 30, wherein said instructions further cause the processing unit to:
34. An apparatus for identifying a work in a digital processing system, comprising:
means for selecting a portion of data of an unknown work;
means for detecting each event in said portion of data of said unknown work;
means for determining a metric between each successive event in said portion of data in said unknown work;
means for generating a list of metrics between said events for said unknown work;
means for comparing said list of metrics for said unknown work to a list of metrics for a known work, wherein the means for comparing comprises
means for receiving said list of metrics of said unknown work and said list of metrics of said known work,
means for determining a number of events in said list of metrics for said unknown work that match events in said list of metrics for said known work, wherein the means for determining the number of events comprises
means for receiving said list of metrics for said unknown work starting at the Mth element,
means for receiving said list of metrics of said known work starting at the Nth element,
means for generating a list of associated pairs wherein each M+X element of said list of metrics for said unknown work is paired with the N+X element of said list of metrics for said known work,
means for computing a regression line through said associated pair in said list of associated pairs,
means for determining a weighted error from said computation of said regression line,
means for comparing said weighted error to a weighted error threshold, and
means for determining a match between said lists responsive to said weighted error being less than said weighted error threshold,
means for determining whether said number at least equals a threshold, and
means for returning a match responsive to said number being at least equal to said threshold; and
means for determining said unknown work is a copy of said known work responsive to a match between said list of metrics of said unknown work and said list of metrics for said known work.
means for comparing said list of metrics of said unknown work to a plurality of lists of metrics wherein each list of metrics is for a known work responsive to a determination that said list of metrics of said unknown work did not match said list of metrics of said known work; and
means for determining said unknown work is a copy of one of said known works responsive to a match of said list of metrics of said unknown work and said one of said plurality of lists that represents said one of said known works.
36. The apparatus of claim 34, wherein said means for determining said number comprises:
means for aligning an Mth element of said list of metrics of said unknown work with an Nth element of said list of metrics for said known work;
means for performing a first comparison of said lists starting from said Mth element in said list of metrics for said unknown list and said Nth element in said list of metrics for said known work;
means for determining whether said lists from said Mth element and said Nth element match; and
means for determining a match responsive to a determination said lists match.
means for recursively determining whether elements of said list of metrics for said unknown work match elements of said list of metrics for said known work.
38. An apparatus for identifying a work in a digital processing system, comprising:
means for comparing said list of metrics for said unknown work to a list of metrics for a known work, wherein the comparing comprises
means for determining a miss ratio from said computation of said regression line,
means for comparing said miss ratio to a miss ratio threshold, and
means for determining a match between said lists responsive to said miss ratio being less than said miss ratio threshold,
40. The apparatus of claim 38, wherein the means for determining said number comprises:
41. The apparatus of claim 38 further comprising:
42. An apparatus for identifying a work in a digital processing system, comprising:
means for determining a weighted miss ratio from said computation of said regression line,
means for comparing said weighted miss ratio to a weighted miss ratio threshold, and
means for determining a match between said lists responsive to said weighted miss ratio being less than said weighted miss ratio threshold,
44. The apparatus of claim 42, wherein the means for determining said number comprises:
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U.S. Classification 726/32, 726/30, 713/176, 726/28, 726/29, 713/177, 726/31
International Classification G06F7/04, H04L9/32, H04L9/00
Cooperative Classification G06F17/30787, G06F2221/074, G06F17/30802, G06F21/10
European Classification G06F17/30V1A, G06F17/30V1V1, G06F21/10
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