US 12,468,838 B2
Adaptive privacy-preserving information retrieval
Pasin Manurangsi, Bangkok (TH); Shanmugasundaram Ravikumar, Piedmont, CA (US); Badih Ghazi, Bangkok (TH); Matthew Tran Clegg, Los Angeles, CA (US); and Joseph Sean Cahill Goodknight Knightbrook, Santa Monica, CA (US)
Assigned to Google LLC, Mountain View, CA (US)
Appl. No. 17/926,281
Filed by Google LLC, Mountain View, CA (US)
PCT Filed Aug. 23, 2022, PCT No. PCT/US2022/041165
§ 371(c)(1), (2) Date Nov. 18, 2022,
PCT Pub. No. WO2024/015085, PCT Pub. Date Jan. 18, 2024.
Claims priority of provisional application 63/389,425, filed on Jul. 15, 2022.
Prior Publication US 2025/0139282 A1, May 1, 2025
Int. Cl. G06F 21/62 (2013.01)
CPC G06F 21/6245 (2013.01) 19 Claims
OG exemplary drawing
 
1. A computer implemented method comprising:
accepting, by an information server and from a user, a request for privacy sensitive information accessible to the information server;
determining, by the information server, a remaining privacy allocation for a user of the information server;
determining, by the information server, a noise parameter for a response to the request, wherein application of the noise parameter to the response decreases a privacy loss associated with the response;
determining, by the information server, a privacy modifier for the response; and
in response to determining, by the information server, that the remaining privacy allocation satisfies the privacy modifier:
determining the response to the request;
applying the noise parameter to the response to produce a noised response;
providing the noised response to the user; and
adjusting the remaining privacy allocation according to the privacy modifier,
wherein the request includes one or more parameters of a truncated discrete Gaussian distribution with a nonzero mean.