US 12,093,977 B2
Attention application user classification privacy
Brendan Eich, Santa Clara, CA (US); Luke Mulks, Dublin, CA (US); Benjamin Livshits, London (GB); Yan Zhu, San Francisco, CA (US); Mandar Shinde, Fremont, CA (US); Nejc Zdovc, Ljubecna (SI); and Brian Johnson, Scottsdale, AZ (US)
Assigned to Brave Software, Inc., San Francisco, CA (US)
Filed by Brave Software, Inc., San Francisco, CA (US)
Filed on Dec. 30, 2022, as Appl. No. 18/091,680.
Application 18/091,680 is a division of application No. 16/436,455, filed on Jun. 10, 2019, granted, now 11,544,737.
Claims priority of provisional application 62/683,001, filed on Jun. 10, 2018.
Claims priority of provisional application 62/683,000, filed on Jun. 10, 2018.
Prior Publication US 2023/0134072 A1, May 4, 2023
Int. Cl. G06Q 30/0242 (2023.01); G06F 3/01 (2006.01); G06Q 30/0251 (2023.01); G06Q 30/0272 (2023.01); G06Q 30/0273 (2023.01); H04L 67/02 (2022.01); H04N 21/442 (2011.01); H04N 21/45 (2011.01); H04N 21/4784 (2011.01)
CPC G06Q 30/0246 (2013.01) [G06F 3/013 (2013.01); G06Q 30/0242 (2013.01); G06Q 30/0254 (2013.01); G06Q 30/0269 (2013.01); G06Q 30/0272 (2013.01); G06Q 30/0273 (2013.01); H04N 21/44204 (2013.01); H04N 21/4532 (2013.01); H04N 21/4784 (2013.01); H04L 67/02 (2013.01)] 4 Claims
OG exemplary drawing
 
1. An attention application advertisement delivery system, the system comprising:
a device that includes at least one hardware device processor; and
a computer readable storage medium storing instructions for execution by the at least one hardware device processor, the instructions, when executed, causing one or more of the at least one hardware device processor to:
receive, from an analytics consumer based at least in part on ads of an ad catalog being serviced to users of a target market via an attention application that locally performs ad matching and user classification, a request for attention analytics on the target market, wherein each ad of the ad catalog hides, from the analytics consumer, respective identities of the users that view the ads on respective attention applications;
receive, from one or more attention applications associated with the users of the target market and via a zero-knowledge proof that hides an attention metric input for a particular user, attention analytics associated with respective users associated with one or more attention applications, wherein receiving the attention analytics via the zero-knowledge proof comprises:
receiving a blinded token from a pool of blinded tokens, wherein the blinded token includes a cryptographic key present in the ad catalog; and
wherein the attention metric input hidden by the zero-knowledge proof is indicative of attention paid, by the particular user, to ads matched and serviced locally by the attention application;
determine, using the attention analytics received via the zero-knowledge proof, attention analytics of the target market with respect to at least one ad in the ad catalog; and
transmit the attention analytics of the target market via a shared ledger, wherein the attention analytics of the target market are accessible by the analytics consumer via the shared ledger using an analytics key.