US 12,113,807 B2
Location-spoofing detection system for a network service
Sheng Yang, Fremont, CA (US); Ze Huang, Santa Clara, CA (US); Qiao Wang, Palo Alto, CA (US); David Spenser DyTang, San Francisco, CA (US); Kiarash Amiri, San Francisco, CA (US); Tara Michelle Mitchell, San Francisco, CA (US); and Xiao Cai, Burlingame, CA (US)
Assigned to Uber Technologies, Inc., San Francisco, CA (US)
Filed by Uber Technologies, Inc., San Francisco, CA (US)
Filed on Aug. 10, 2023, as Appl. No. 18/232,488.
Application 18/232,488 is a continuation of application No. 17/204,506, filed on Mar. 17, 2021, granted, now 11,777,954.
Application 17/204,506 is a continuation of application No. 16/155,382, filed on Oct. 9, 2018, granted, now 10,999,299, issued on May 4, 2021.
Prior Publication US 2023/0388318 A1, Nov. 30, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 9/40 (2022.01); H04W 12/12 (2021.01); H04W 12/63 (2021.01); G01S 19/21 (2010.01)
CPC H04L 63/1408 (2013.01) [H04L 63/1466 (2013.01); H04W 12/12 (2013.01); H04W 12/63 (2021.01); G01S 19/215 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing system operating an application service, comprising:
a network communication interface to communicate, over one or more networks, with computing devices of drivers;
one or more processors; and
one or more memory resources storing instructions that, when executed by the one or more processors, cause the computing system to:
receive, over the one or more networks, location data from the computing devices, each of the computing devices operating a designated application associated with the application service;
based at least in part on the location data received from a computing device of a respective driver, execute a location-based feasibility model to determine that one or more anomalous locational attributes are present in the location data of the respective driver, wherein the location-based feasibility model outputs a probability that the computing device of the respective driver is performing location-spoofing; and
based on the probability indicating that the computing device of the respective driver is performing location-spoofing, associate a data set with a driver profile of the respective driver.