US 11,909,752 B1
Detecting deviations from typical user behavior
Vikram Kapoor, Cupertino, CA (US); Harish Kumar Bharat Singh, Pleasanton, CA (US); Weifei Zeng, Sunnyvale, CA (US); Vimalkumar Jeyakumar, Los Altos, CA (US); Theron Tock, Mountain View, CA (US); Ying Xie, Cupertino, CA (US); and Yijou Chen, Cupertino, CA (US)
Assigned to LACEWORK, INC., Mountain View, CA (US)
Filed by LACEWORK, INC., San Jose, CA (US)
Filed on Jul. 5, 2022, as Appl. No. 17/857,896.
Application 17/857,896 is a continuation of application No. 17/704,926, filed on Mar. 25, 2022, abandoned.
Application 17/704,926 is a continuation in part of application No. 17/196,887, filed on Mar. 9, 2021, granted, now 11,689,553.
Application 17/196,887 is a continuation of application No. 16/459,207, filed on Jul. 1, 2019, granted, now 10,986,114, issued on Apr. 20, 2021.
Application 16/459,207 is a continuation of application No. 16/134,821, filed on Sep. 18, 2018, granted, now 10,419,469, issued on Sep. 17, 2019.
Claims priority of provisional application 63/240,818, filed on Sep. 3, 2021.
Claims priority of provisional application 62/650,971, filed on Mar. 30, 2018.
Claims priority of provisional application 62/590,986, filed on Nov. 27, 2017.
Int. Cl. H04L 29/06 (2006.01); H04L 9/40 (2022.01); G06F 16/9038 (2019.01); G06F 9/455 (2018.01); H04L 43/06 (2022.01); G06F 16/9535 (2019.01); G06F 16/901 (2019.01); G06F 21/57 (2013.01); H04L 43/045 (2022.01); H04L 67/306 (2022.01); H04L 67/50 (2022.01); G06F 9/54 (2006.01); G06F 16/9537 (2019.01); G06F 16/2455 (2019.01)
CPC H04L 63/1425 (2013.01) [G06F 9/455 (2013.01); G06F 9/545 (2013.01); G06F 16/9024 (2019.01); G06F 16/9038 (2019.01); G06F 16/9535 (2019.01); G06F 16/9537 (2019.01); G06F 21/57 (2013.01); H04L 43/045 (2013.01); H04L 43/06 (2013.01); H04L 63/10 (2013.01); H04L 67/306 (2013.01); H04L 67/535 (2022.05); G06F 16/2456 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A method of detecting deviations from typical user behavior, the method comprising:
identifying a location of a device that is associated with a user;
determining device activity associated with the user;
detecting, based on a profile associated with the user, that the device activity associated with the user deviates from normal activity for the user; and
generating a user-specific visualization for the user, the user-specific visualization including a first visual representation of the location of the device, and one or more second visual representations of the device activity associated with the user linked to the first visual representation of the location of the device indicating that the device activity occurred at the location, wherein the user-specific visualization further includes one or more alerts.