METHOD AND SYSTEM FOR EVALUATING AND SELECTING TRACEROUTES TO BE USED IN DETERMINING THE GEOGRAPHIC LOCATION OF A NETWORK BLOCK

• US 20090144411A1
• Filed: 11/30/2007
• Published: 06/04/2009
• Est. Priority Date: 11/30/2007
• Status: Active Grant

• Current Assignee: NeuStar IP Intelligence, Inc. (Neustar Incorporated)
• Original Assignee: Quova Inc. (Neustar Incorporated)
• Inventors: Speckbacher, Tobias, Winkler, Adam, Conner, Gary
• Granted Patent: US 8,055,792 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: H04L 2463/101 applying security measures for digital rights management
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources
• CPC Class Codes: H04L 63/107 wherein the security policies are location-dependent, e.g. entities privileges depend on current location or allowing specific operations only from locally connected terminals
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

Described herein are a method and system for evaluating and selecting traceroutes to be used in determining the geographic location of a network block. A particular embodiment of the system includes a set of traceroute feature vector extractors, each traceroute feature vector extractor being associated with at least one of a plurality of traceroutes, each traceroute feature vector extractor being configured to generate a traceroute feature vector for at least one of the plurality of traceroutes; a set of traceroute classifiers each coupled to at least one of the traceroute feature vector extractors, each traceroute classifier being associated with at least one of the plurality of traceroutes, each traceroute classifier being configured to generate at least one traceroute classification and/or regression based on at least one of the traceroute feature vectors; and a traceroute geolocation determining engine to determine a geographic location of a network block based on the at least one traceroute classification and/or regression generated by the set of traceroute classifiers.

Claims

1. A method of determining a geographic location of a network block comprising:

obtaining geo-location data associated with a plurality of traceroutes, each traceroute corresponding to a data path through a plurality of network nodes;

generating, for each of the plurality of traceroutes, a traceroute feature vector;

classifying and/or regressing each of the plurality of traceroutes to generate traceroute classifications and/or regressions based on the traceroute feature vectors; and

determining a geographic location of the network block based upon at least one of the traceroute classifications and/or regressions.

2. The method of claim 1 wherein each of the plurality of traceroutes may be complete or incomplete traceroutes.

3. The method of claim 1 wherein the determined geographic location is associated with a best traceroute classification and/or regression.

4. The method of claim 1 including providing a plurality of traceroute data collectors, each being associated with at least one of the plurality of traceroutes.

5. The method of claim 4 including providing a plurality of traceroute classifiers, each being associated with at least one of the plurality of traceroute feature vectors.

6. The method of claim 5 including providing a traceroute geolocation determining engine that receives input from the plurality of traceroute classifiers.

7. The method of claim 1 wherein the geographic location is assigned on a country level, a state level, a city level, a zip code level, and/or a specific coordinate level.

8. The method of claim 1 including using supervised learning techniques to classify and/or regress each of the plurality of traceroutes to generate traceroute classifications and/or regressions based on the traceroute feature vectors and training data.

9. The method of claim 1 wherein the determined geographic location of the network block is based upon an interpolation between at least two of the traceroute assignment classifications and/or regressions.

10. The method of claim 1 including using autonomous system penetration data of each traceroute in generating each traceroute'"'"'s feature vector.

11. A network block geo-locator system comprising:

a set of traceroute feature vector extractors, each traceroute feature vector extractor being associated with at least one of a plurality of traceroutes, each traceroute feature vector extractor being configured to generate a traceroute feature vector for at least one of the plurality of traceroutes;

a set of traceroute classifiers each coupled to at least one of the traceroute feature vector extractors, each traceroute classifier being associated with at least one of the plurality of traceroutes, each traceroute classifier being configured to generate at least one traceroute classification and/or regression based on at least one of the traceroute feature vectors; and

a traceroute geolocation determining engine to determine a geographic location of a network block based on the at least one traceroute classification and/or regression generated by the set of traceroute classifiers.

12. The network block geo-locator system of claim 11 wherein each of the plurality of traceroutes may be complete or incomplete traceroutes.

13. The network block geo-locator system of claim 11 wherein the determined geographic location is associated with a best traceroute classification and/or regression.

14. The network block geo-locator system of claim 11 wherein the geographic location includes information associated with a country level, a state level, a city level, a zip code level, and/or a specific coordinate level.

15. The network block geo-locator system of claim 11 wherein the determined geographic location of the network block is based upon an interpolation between at least two of the traceroute classifications and/or regressions.

16. The network block geo-locator system of claim 11 including using autonomous system penetration data of each traceroute in generating each traceroute'"'"'s feature vector.

17. An article of manufacture comprising a machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a machine, cause the machine to:

obtain geo-location data associated with a plurality of traceroutes, each traceroute corresponding to a data path through a plurality of network nodes;

generate, for each of the plurality of traceroutes, a traceroute feature vector;

classify and/or regress each of the plurality of traceroutes to generate traceroute classifications and/or regressions based on the traceroute feature vectors; and

determine a geographic location of the network block based upon at least one of the traceroute classifications and/or regressions.

18. The article of manufacture of claim 17 wherein the determined geographic location is associated with a best traceroute classification and/or regression.

19. The article of manufacture of claim 17 being further configured to provide a plurality of traceroute data collectors, each being associated with at least one of the plurality of traceroutes.

20. The article of manufacture of claim 19 being further configured to provide a plurality of traceroute classifiers, each being associated with at least one of the plurality of traceroute feature vectors.

21. The article of manufacture of claim 20 being further configured to provide a traceroute geolocation determining engine that receives input from the plurality of traceroute classifiers.

22. The article of manufacture of claim 17 wherein the geographic location is assigned on a country level, a state level, a city level, a zip code level, and/or a specific coordinate level.