Computerized, copy detection and discrimination apparatus and method

• US 8,909,733 B2
• Filed: 02/14/2011
• Issued: 12/09/2014
• Est. Priority Date: 05/15/2007
• Status: Active Grant

• Current Assignee: Phillip M. Adams
• Original Assignee: Phillip M. Adams
• Inventors: Adams, Phillip M.
• Primary Examiner(s): Winder, Patrice
• Assistant Examiner(s): Chang, Julian
• Application Number:
  US13/026,951
• Publication Number:
  US 20110173340A1
• Time in Patent Office: 1,394 Days
• Field of Search: 726 22- 33, 380201-204, 709217-219
• US Class Current: 709/217
• CPC Class Codes: G06F 21/10 Protecting distributed programs or content, e.g. vending or licensing of copyrighted material protection in video systems or pay television H04N7/16 ; Digital rights management [DRM]
• CPC Class Codes: G06F 21/105 Arrangements for software license management or administration, e.g. for managing licenses at corporate level
• CPC Class Codes: G06F 21/16 Program or content traceability, e.g. by watermarking
• CPC Class Codes: G06Q 50/184 Intellectual property management
• CPC Class Codes: H04L 2209/605 Copy protection
• CPC Class Codes: H04L 2209/606 Traitor tracing
• CPC Class Codes: H04L 2209/608 Watermarking
• CPC Class Codes: H04L 2463/103 applying security measure for protecting copyright
• CPC Class Codes: H04L 43/08 Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 63/0245 Filtering by information in the payload
• CPC Class Codes: H04L 63/1408 by monitoring network traffic monitoring network traffic per se H04L43/00
• CPC Class Codes: Y10S 705/904 Usage protection of distributed files
• CPC Class Codes: Y10S 705/908 Software or content usage protection
• CPC Class Codes: Y10S 705/911 Copy protection or prevention

Abstract

An engine identifying segments or portions of one source material or source file common to or found in another source material or file. The engine may receive a first data stream in binary form as well as a second stream in binary form. The engine may include a data stream processor or pre-processor programmed to translate the first and second data streams to generate respective first and second processed data streams. The commonality between the first and second processed data streams may be greater than the commonality between the first and second data streams themselves. Also, a comparator may be programmed to compare the first and second process data streams and identify binary segments found in both the first and second processed data streams.

Claims

1. A system comprising:

one or more central processing units (CPUs) and one or more memory devices operably coupled to the one or more CPUs, the one or more memory devices, the one or more CPUs and one or more memory devices implementing—

a data stream processor programmed to receive a first data stream consisting of first digital traffic on a network;

the data stream processor further programmed to receive a second data stream consisting of second digital traffic on a network;

the data stream processor further programmed to translate the first and second data streams to generate respective first and second processed data streams, commonality between the first and second processed data streams being greater than the commonality between the first and second data streams; and

a comparator programmed to compare the first and second processed data streams and identify segments common to both the first and second processed data streams;

wherein;

the data stream processor is further programmed to execute at least one method to identify first and second samples selected from the first and second data streams, respectively;

the data stream processor is further programmed to translate the first and second samples to generate the first and second processed data streams;

the first and second samples are selected using load maps of executable software in the first and second data streams.

2. The system of claim 1, further comprising a user interface programmed to communicate instructions from a user to the data stream processor to select which method of the at least one method is executed by the data stream processor.

3. The system of claim 2, where a first method of the at least one method comprises selecting the entire first data stream as the first sample and the entire second data stream as the second sample.

4. The system of claim 3, wherein a second method of the at least one method comprises:

executing the first data stream and recording in real time the processing instructions executed thereby as the first sample; and

executing the second data stream and recording in real time the processing instructions executed thereby as the second sample.

5. The system of claim 4, wherein:

the first processed data stream comprises the first data stream translated into register transfer language; and

the second processed data stream comprises the second data stream translated into register transfer language.

6. The system of claim 5, wherein:

the first processed data stream comprises a de-optimized version of the first data stream; and

the second processed data stream comprises a de-optimized version of the second data stream.

7. The system of claim 6, further comprising a post-identification data stream processor programmed to convert the binary segments into digital sound recording files.

8. The system of claim 1, wherein:

the first processed data stream comprises at least a portion of a real time recording of the processing instructions executed by executing the first data stream; and

the second processed data stream comprises at least a portion of a real time recording of the processing instructions executed by executing the second data stream.

9. The system of claim 1, wherein:

the first processed data stream comprises the first data stream translated into register transfer language; and

the second processed data stream comprises the second data stream translated into register transfer language.

10. The system of claim 1, wherein:

the first processed data stream comprises a de-optimized version of the first data stream; and

the second processed data stream comprises a de-optimized version of the second data stream.

11. The system of claim 1, further comprising a post-identification data stream processor programmed to convert the segments into digital sound recording files.

12. The system of claim 1, further comprising a user interface programmed to communicate instructions from a user to the comparator to specify a minimum length of the segments identified.

13. A system comprising:

one or more central processing units (CPUs) and one or more memory devices operably coupled to the one or more CPUs, the one or more memory devices, the one or more CPUs and one or more memory devices implementing—

a data stream processor programmed to receive a first data stream consisting of first digital traffic on a digital network;

the data stream processor further programmed to receive a second data stream consisting of second digital traffic on the digital network;

the data stream processor further programmed to translate the first and second data streams to generate respective first and second processed data streams, commonality between the first and second processed data streams being greater than the commonality between the first and second data streams when each of the first and second processed data streams is represented in a register transfer language; and

a comparator, programmed to compare the first and second processed data streams and identify segments common to both the first and second processed data streams;

wherein;

the data stream processor is further programmed to execute at least one method to identify first and second samples selected from the first and second data streams, respectively; and

the data stream processor is further programmed to translate the first and second samples to generate the first and second processed data streams

the first and second samples are selected using load maps of executable software in the first and second data streams.

14. The system of claim 13, wherein the network is the Internet.

15. A method to analyze digital data streams retrieved from a digital network, the method comprising, by one or more central processing units (CPUs) and one or more memory devices operably coupled to the one or more CPUs, performing:

selecting a data stream processor programmed to receive a first data stream consisting of network digital traffic and a second data stream consisting of other network digital traffic;

connecting the data stream processor to a first digital network;

selecting the first data stream from first digital traffic traveling on the first digital network;

selecting the second data stream from a second digital traffic selected from data on one of the first digital network and a second digital network, distinct from the first network;

characterizing commonality between the first and second data streams by the data stream processor generating first and second processed data streams consisting of translations of the first and second data streams, respectively, a first commonality reflecting a first mathematically recognized pattern characterizing a relation between the first and second data streams is less than a second commonality reflecting a second mathematically recognized pattern characterizing a relation between the first and second processed data streams; and

identifying, by a comparator functioning independently from sample rate, segments common to both the first and second data streams by comparing directly corresponding segments from the first and second processed data streams;

wherein;

the data stream processor is further programmed to execute at least one method to identify first and second samples selected from the first and second data streams, respectively;

the data stream processor is further programmed to translate the first and second samples to generate the first and second processed data streams; and

the first and second samples are selected using load maps of executable software in the first and second data streams.