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 computing device within a computing network over the Internet, the method comprising:
receiving a plurality of requests from at least one computing device, over the Internet, at a server comprising a communication channel and a data storage device;
analyzing the plurality of requests to determine a plurality of sequential request features of requests received at different times, wherein the request features are obtained from a plurality of computing devices associated with different device fingerprints, wherein at least some of the request features are identical, wherein each request feature comprises at least a session identifier, and wherein the analyzing comprises:
identifying timing patterns in identical session identifiers; and
determining a number of unique computing devices, of the one or more computing devices, based upon a degree of interlacement of session identifiers in the received plurality of requests; and
determining, from the identified timing patterns and the determined number of unique computing devices, whether one or more requests, of the received plurality of requests, originates from one or more computing devices, of the plurality of computing devices, within the network.
2. The method of claim 1 , wherein each request feature further comprises a domain, a subdomain, or a URL, and wherein the analyzing further comprises identifying timing patterns in identical domains, subdomains, or URLs.
3. The method of claim 1 , wherein analyzing a plurality of sequential request features further comprises identifying unique cookies or shared persistent object cookies associated with respective requests.
4. The method of claim 1 , wherein analyzing a plurality of sequential request features further comprises analyzing a pattern of websites associated with the at least one computing device.
5. The method of claim 1 , further comprising:
determining whether a request, of the plurality of requests, originates from a computing device within the computing network; and
requesting additional information, in response to determining that the request originates from the computing device within the computing network, from the computing device associated with the request.
6. A system for identifying a computing device within a computing network, the system comprising:
at least one data storage device storing instructions for identifying computing devices;
at least one processor configured to execute the instructions to perform operations for identifying the computing devices, the operations comprising:
receiving a plurality of requests from at least one computing device, over the Internet, at a server comprising a communication channel and a data storage device;
analyzing the plurality of requests to determine a plurality of sequential request features of requests received at different times, wherein the request features are obtained from a plurality of computing devices associated with different device fingerprints, wherein at least some of the request features are identical, wherein each request feature comprises at least a session identifier, and wherein the analyzing comprises:
identifying timing patterns in identical session identifiers; and
determining a number of unique computing devices, of the one or more computing devices, based upon a degree of interlacement of session identifiers in the received plurality of requests; and
determining from the identified timing patterns and the determined number of unique computing devices, whether one or more requests, of the received plurality of requests, originates from one or more computing devices, of the plurality of computing devices, within the network.
7. The system of claim 6 , wherein each request feature further comprises a domain, subdomain or URL and wherein the analyzing further comprises identifying timing patterns in identical domains, subdomains or URLs.
8. The system of claim 6 , wherein analyzing a plurality of sequential request features further comprises identifying unique cookies or shared persistent object cookies.
9. The system of claim 6 , wherein analyzing a plurality of sequential request features further comprises analyzing a pattern of websites associated with the at least one computing device.
10. The system of claim 6 , wherein the operations further comprise:
determining whether a request of the plurality of requests, originates from a computing device within the computing network; and
requesting additional information, in response to determining that the request originates from the computing device within the computing network, from the computing device associated with the request.
11. 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:
receiving a plurality of requests from at least one computing device, over the Internet, at a server comprising a communication channel and a data storage device;
analyzing the plurality of requests to determine a plurality of sequential request features of requests received at different times, wherein the request features are obtained from a plurality of computing devices associated with different device fingerprints, wherein at least some of the request features are identical, wherein each request feature comprises at least a session identifier, and wherein the analyzing comprises:
identifying timing patterns in identical session identifiers; and
determining a number of unique computing devices, of the one or more computing devices, based upon a degree of interlacement of session identifiers in the received plurality of requests; and
determining, from the identified timing patterns and the determined number of unique computing devices, whether one or more requests, of the received plurality of requests, originates from one or more computing devices, of the plurality of computing devices, within the network.
12. The non-transitory computer-readable medium of claim 11 , wherein each request feature further comprises a domain, subdomain or URL and wherein the analyzing further comprises identifying timing patterns in identical domains, subdomains or URLs.
13. The non-transitory computer-readable medium of claim 11 , wherein analyzing a plurality of sequential request features further comprises identifying unique cookies or shared persistent object cookies.
14. The non-transitory computer-readable medium of claim 11 , wherein analyzing a plurality of sequential request features further comprises analyzing a pattern of websites associated with the at least one computing device.
15. The non-transitory computer-readable medium of claim 11 , wherein the method further comprises:
determining whether a request, of the plurality of requests, originates from a computing device within the computing network; and
requesting additional information, in response to determining that the request originates from the computing device within the computing network, from the computing device associated with the request.