Systems and methods for identifying a returning web client
Methods and systems are provided for identifying unique devices and/or unique users of a web-based system within constraints of an external application. In some embodiments the process comprises receiving request information from a client device at an application server, using such information to form a device fingerprint, and attempting to match the newly-formed fingerprint with exactly one fingerprint stored in a database of previously-formed fingerprints. Some embodiments utilize a two-stage Locality-Sensitive Hash query technique. The client device fingerprint may be converted into a series of LSH values which may be used to find a matching fingerprint. A first stage may query input LSH values against LSH values in a data store, and a second stage may query LSH values temporarily held in volatile memory, thereby minimizing network traffic and reducing a total process time.
1. A method of identifying a client computing device, the method comprising:
performing a first query against a data store comprising a plurality of stored hashed values associated with a plurality of stored device fingerprints, each stored device fingerprint identifying a particular computing device, wherein performing the first query comprises identifying broad hashed values, from a plurality of input hashed values, which are common to a first number of device fingerprints of the plurality of stored device fingerprints;
performing a second query against returned hashed values from the first query, wherein performing the second query comprises identifying at least one narrow hashed value, from the plurality of input hashed values, that is common to a second number of device fingerprints, of the plurality of stored device fingerprints; and
based on responses to the first query and the second query, identifying a most closely matching device fingerprint.
2. The method of claim 1 , wherein the identifying the broad hashed values that are common to the first number of device fingerprints of the plurality of stored device fingerprints includes identifying broad hashed values matched within a desired degree of similarity.
3. The method of claim 2 , wherein the identifying the at least one narrow hashed value that is common to the second number of device fingerprints of the plurality of stored device fingerprints includes identifying at least one narrow hashed value matched within a desired degree of similarity.
4. The method of claim 1 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest number of query hits resulting from the first query and the second query.
5. The method of claim 1 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest weighted number of query hits resulting from the first query and the second query, wherein the number of query hits resulting from the first query is weighted differently than the number of query hits resulting from the second query.
6. The method of claim 1 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest weighted number of query hits resulting from the first query and the second query, wherein the number of query hits resulting from the second query is weighted based on a visit history corresponding to a candidate device fingerprint.
7. The method of claim 1 , further comprising identifying the client computing device based on the most closely matching device fingerprint.
8. A system for identifying a computing device within a computing network, the system comprising:
a data storage device;
a server comprising a communication channel with the data storage device, the server having program code that, when executed by a processor, executes a method comprising:
performing a first query against a data store comprising a plurality of stored hashed values associated with a plurality of stored device fingerprints, each stored device fingerprint identifying a particular computing device, wherein performing the first query comprises identifying broad hashed values, from a plurality of input hashed values, which are common to a first number of device fingerprints of the plurality of stored device fingerprints;
performing a second query against returned hashed values from the first query, wherein performing the second query comprises identifying at least one narrow hashed value, from the plurality of input hashed values, that is common to a second number of device fingerprints, of the plurality of stored device fingerprints; and
based on responses to the first query and the second query, identifying a most closely matching device fingerprint.
9. The system of claim 8 , wherein the identifying the broad hashed values that are common to the first number of device fingerprints of the plurality of stored device fingerprints includes identifying broad hashed values matched within a desired degree of similarity.
10. The system of claim 9 , wherein the identifying the at least one narrow hashed value that is common to the second number of device fingerprints of the plurality of stored device fingerprints includes identifying at least one narrow hashed value matched within a desired degree of similarity.
11. The system of claim 8 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest number of query hits resulting from the first query and the second query.
12. The system of claim 8 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest weighted number of query hits resulting from the first query and the second query, wherein the number of query hits resulting from the first query is weighted differently than the number of query hits resulting from the second query.
13. The system of claim 8 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest weighted number of query hits resulting from the first query and the second query, wherein the number of query hits resulting from the second query is weighted based on a visit history corresponding to a candidate device fingerprint.
14. The system of claim 8 , wherein the method further comprises identifying the client computing device based on the most closely matching device fingerprint.
15. A non-transitory computer-readable medium storing instructions that when executed by a computer system, cause the computer system to perform a method of identifying a computing device within a computing network, the method comprising:
performing a first query against a data store comprising a plurality of stored hashed values associated with a plurality of stored device fingerprints, each stored device fingerprint identifying a particular computing device, wherein performing the first query comprises identifying broad hashed values, from a plurality of input hashed values, which are common to a first number of device fingerprints of the plurality of stored device fingerprints;
performing a second query against returned hashed values from the first query, wherein performing the second query comprises identifying at least one narrow hashed value, from the plurality of input hashed values, that is common to a second number of device fingerprints, of the plurality of stored device fingerprints; and
based on responses to the first query and the second query, identifying a most closely matching device fingerprint.
16. The non-transitory computer-readable medium of claim 15 , wherein the identifying the broad hashed values that are common to the first number of device fingerprints of the plurality of stored device fingerprints includes identifying broad hashed values matched within a desired degree of similarity.
17. The non-transitory computer-readable medium of claim 16 , wherein the identifying the at least one narrow hashed value that is common to the second number of device fingerprints of the plurality of stored device fingerprints includes identifying at least one narrow hashed value matched within a desired degree of similarity.
18. The non-transitory computer-readable medium of claim 15 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest number of query hits resulting from the first query and the second query.
19. The non-transitory computer-readable medium of claim 15 , wherein identifying the most closely matching device fingerprint comprises identifying a candidate device fingerprint having a greatest weighted number of query hits resulting from the first query and the second query, wherein the number of query hits resulting from the first query is weighted differently than the number of query hits resulting from the second query.
20. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises identifying the client computing device based on the most closely matching device fingerprint.