Method for statistical object identification
The present invention provides a mechanism to communicate an original object ( 12 S) without requiring the sending of the complete original object. A representative of the original object ( 12 S), a statistical object ( 14 S), is generated by one entity and is communicated to a second entity. The second entity receives the statistical object ( 14 S), and identifies it as being generated from an original object ( 12 S). If the second entity is unable to unambiguously identify the statistical object ( 14 S), the second entity records the partial identity progress and associated communications characteristics information ( 22 ). The amount of information communicated during this process is much smaller than the original object ( 12 S), greatly improving the speed and efficiency of communicating an original object ( 12 S).
1. A method comprising the steps of:
providing a device ( 10 ) for generating a plurality of statistical objects ( 14 P) based upon a plurality of original objects ( 12 P);
each of said plurality of statistical objects ( 14 P) being a statistical representation of one of said plurality of original objects ( 12 P);
said plurality of original objects ( 12 P) and said plurality of statistical objects ( 14 P) being stored in a table;
using a communications receiver ( 32 ) to receive a first statistical object ( 14 F) having communications characteristics ( 22 );
using a statistical object matcher ( 18 ) to determine if said first statistical object ( 14 F) matches at least one of said plurality of statistical objects ( 14 P);
using an accumulated statistical object selector ( 20 ) to obtain and accumulate said first statistical object ( 14 F) and a plurality of matched statistical objects ( 14 MP) in an accumulated statistical object ( 14 A) identified by said communications characteristics ( 22 );
using an original object identifier ( 26 ) to determine if said accumulated statistical object ( 14 A) can be produced by exactly one original object ( 12 S) of said plurality of original objects ( 12 P);
selecting that original object ( 12 S) from said plurality of original objects ( 12 P);
using a probability calculator ( 30 ) to determine a calculated probability ( 36 ) of guessing said accumulated statistical object ( 14 A) based on said accumulated statistical object ( 14 A) and the number of statistical objects in said plurality of said statistical objects ( 14 P);
using a threshold comparator ( 32 ) to determine if said calculated probability ( 36 ) is less than a threshold value ( 27 ); and
providing an indication ( 34 ) of said selected original object ( 12 SEL).
2. A method as recited in claim 1 , in which:
the probability of guessing said first statistical object ( 14 F) remains constant, while the number of statistical objects in said plurality of statistical objects ( 14 P) varies.
3. A method as recited in claim 1 , in which:
the probability of guessing said accumulated statistical object ( 14 A) remains constant, while the number of statistical objects in said plurality of statistical objects ( 14 P) varies.
4. A method as recited in claim 1 , in which:
said accumulated statistical object ( 14 A) in said plurality of accumulated statistical objects ( 14 AP) is removed after a period of inactivity pertaining to said accumulated statistical object ( 14 A).
5. A method as recited in claim 1 , in which:
said threshold value ( 27 ) can be changed without coordination with the source of said first statistical object ( 14 F).
6. A method as recited in claim 1 , in which:
said threshold value ( 27 ) can be changed without communication with the source of said first statistical object ( 14 F).
7. A method as recited in claim 1 , in which:
said threshold value ( 27 ) is associated with said selected original object ( 12 SEL).
8. A method as recited in claim 1 , in which:
said threshold value ( 27 ) is associated with said device ( 10 ).
9. A method as recited in claim 1 , in which:
said threshold value ( 27 ) is associated with a plurality of original objects ( 12 P).
10. A method as recited in claim 1 , in which:
said indication ( 34 ) includes clock information used in the generation of said first statistical object ( 14 F).
11. A method as recited in claim 1 , in which:
said indication ( 34 ) includes keying information used in the generation of said first statistical object ( 14 F).
12. A method as recited in claim 1 , in which:
said indication ( 34 ) includes state information used in the generation of said first statistical object ( 14 F).
13. A method as recited in claim 1 , in which:
said indication ( 34 ) includes additional information used in the generation of said first statistical object ( 14 F).
14. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes TCP/IP session information.
15. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes addressing information.
16. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes security association information.
17. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes frequency information.
18. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes phase information.
19. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes time information.
20. A method as recited in claim 1 , in which:
said communications characteristics ( 22 ) includes amplitude information.
21. A method comprising the steps of:
providing a device ( 10 ) for generating a plurality of statistical objects ( 14 P) based upon a plurality of original objects ( 12 P);
each of said plurality of statistical objects ( 14 P) being a statistical representation of one of said plurality of original objects ( 12 P);
said plurality of original objects ( 12 P) and said plurality of statistical objects ( 14 P) being stored in a table;
receiving with a communications receiver ( 16 ) a first statistical object ( 14 F) having communications characteristics ( 22 );
determining with a statistical object matcher ( 18 ) if said first statistical object ( 14 F) matches at least one of said plurality of statistical objects ( 14 P);
obtaining and accumulating with an accumulated statistical object selector ( 20 ) said first statistical object ( 14 F) and a plurality of matching statistical objects ( 14 MP) in an accumulated statistical object ( 14 A) identified by said communications characteristics ( 22 );
selecting with an associated original object selector ( 24 ) a selected original object ( 12 SEL) identified by said communications characteristics ( 22 );
determining with associated original object identifier ( 28 ) if said accumulated statistical object ( 14 A) can be produced by said selected original object ( 12 SEL);
determining with a probability calculator ( 30 ) the calculated probability ( 36 ) of guessing said accumulated statistical object ( 14 A) based on said accumulated statistical object ( 14 A) and the number of statistical objects in said plurality of said statistical objects ( 14 P) produced by original objects associated with said associated communications characteristics ( 22 );
determining with a threshold comparator ( 32 ) if said calculated probability ( 36 ) is less than a probability threshold value ( 27 );
associating said communications characteristics ( 22 ) with said selected original object ( 12 SEL); and
providing an indication ( 34 ) of said selected original object ( 12 SEL).
22. A method as recited in claim 21 , in which:
the probability of guessing said first statistical object ( 14 F) remains constant while the number of statistical objects in said plurality of statistical objects ( 14 P) varies.
23. A method as recited in claim 21 , in which:
the probability of guessing said accumulated statistical object ( 14 A) remains constant, while the number of statistical objects in said plurality of statistical objects ( 14 P) varies.
24. A method as recited in claim 21 , in which:
said accumulated statistical object ( 14 A) in said plurality of accumulated statistical objects ( 14 A) is removed after a period of inactivity pertaining to said accumulated statistical object ( 14 A).
25. A method as recited in claim 21 , in which:
said association of communications characteristics ( 22 ) with said original object ( 12 S) is removed after a period of inactivity pertaining to said communications criteria ( 22 ).
26. A method as recited in claim 21 , in which:
said association of communications criteria ( 22 ) with said original object ( 12 S) is removed after a period of inactivity pertaining to said original object ( 12 S).
27. A method as recited in claim 21 , in which:
said association of communications criteria ( 22 ) with said original object ( 12 S) is created prior to receiving a first statistical object ( 14 F).
28. A method as recited in claim 21 , in which:
said probability threshold value ( 27 ) can be changed without coordination with the source of said first statistical object ( 14 F).
29. A method as recited in claim 21 , in which:
said probability threshold value ( 27 ) can be changed without communication with the source of said first statistical object ( 14 F).
30. A method as recited in claim 21 , in which:
said probability threshold value ( 27 ) is associated with said selected original object ( 26 ).
31. A method as recited in claim 21 , in which:
said probability threshold value ( 27 ) is associated with said device ( 10 ).
32. A method as recited in claim 21 , in which:
said probability threshold value ( 27 ) is associated with a plurality of original objects.
33. A method as recited in claim 21 , in which:
said indication ( 34 ) includes clock information used in the generation of said first statistical object ( 14 F).
34. A method as recited in claim 21 , in which:
said indication ( 34 ) includes keying information used in the generation of said first statistical object ( 14 F).
35. A method as recited in claim 21 , in which:
said indication ( 34 ) includes state information used in the generation of said first statistical object ( 14 F).
36. A method as recited in claim 21 , in which:
said indication ( 34 ) includes additional information used in the generation of said first statistical object ( 14 F).
37. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes TCP/IP session information.
38. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes addressing information.
39. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes security association information.
40. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes frequency information.
41. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes phase information.
42. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes time information.
43. A method as recited in claim 21 , in which:
said communications characteristics ( 22 ) includes amplitude information.