US 12,034,724 B2
Adverse user behavior detection and mitigation
Kristopher Aaron Makey, Kirkland, WA (US); Alexis Descre, Seattle, WA (US); Donald T. Sprague, Seattle, WA (US); William Sean Sheehan, Seattle, WA (US); Warren Michael Alpert, Cambridge, MA (US); Robert Mitchell Smith, Seattle, WA (US); and Arnav Kumar Agrawal, Bellevue, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing LLC, Redmond, WA (US)
Filed on Nov. 4, 2020, as Appl. No. 17/089,336.
Prior Publication US 2022/0141223 A1, May 5, 2022
Int. Cl. H04L 9/40 (2022.01); G06Q 50/00 (2012.01)
CPC H04L 63/10 (2013.01) [G06Q 50/01 (2013.01); H04L 63/1425 (2013.01)] 13 Claims
OG exemplary drawing
 
1. A system comprising:
at least one processor; and
memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations, the set of operations comprising:
receiving a request to follow a target user account of a social platform, wherein the request is associated with a requesting user account;
evaluating a trust metric associated with the requesting user account based on a threshold to determine whether the requesting user account is a trusted user account of the social platform, wherein the trust metric corresponds to a set of signals associated with the requesting user account;
when it is determined that the requesting user account is a trusted user account, adding the requesting user account to a set of followers of the target user account; and
when it is determined that the requesting user account is not a trusted user account, updating a buffer data structure based on the request to follow the target user account, wherein the buffer data structure is different than the set of followers of the target user account, thereby buffering the request to follow the target user account.