US 12,457,110 B2
Geospatial-temporal pathogen tracing in zero knowledge
Daniel Alan Gregory, Cypress, TX (US); Prithwish Basu, Lowell, MA (US); Zachary Ratliff, Somerville, MA (US); Siddharth Pal, Waltham, MA (US); Kimberly Gavin, Glen Echo, MD (US); Benjamin Montgomery, Cambridge, MA (US); and Joud Khoury, Boston, MA (US)
Assigned to RTX BBN TECHNOLOGIES, INC., Cambridge, MA (US)
Filed by Raytheon BBN Technologies Corp., Cambridge, MA (US)
Filed on Jun. 30, 2021, as Appl. No. 17/364,048.
Claims priority of provisional application 63/046,815, filed on Jul. 1, 2020.
Prior Publication US 2022/0006635 A1, Jan. 6, 2022
Int. Cl. H04L 9/32 (2006.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/80 (2018.01); G16H 70/60 (2018.01); H04W 4/029 (2018.01)
CPC H04L 9/3221 (2013.01) [G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/80 (2018.01); G16H 70/60 (2018.01); H04L 9/3218 (2013.01); H04W 4/029 (2018.02)] 17 Claims
OG exemplary drawing
 
1. One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
generating, by a first user device, a first proximity token for contact tracing, wherein the first proximity token is generated according to a schedule and based on a random string associated with the first user device;
receiving, by the first user device, a second proximity token from a second user device, wherein the second proximity token is generated according to the schedule and based on a random string associated with the second user device;
sorting, by the first user device, the first proximity token and the second proximity token according to a sorting criteria used by both the first user device and the second user device;
generating, by the first user device, a first hash based on:
the first proximity token and the second proximity token; and
the sorting of the first proximity token and the second proximity token;
generating, by the first user device using a prover function of a preprocessing zero knowledge succinct non-interactive argument of knowledge (pp-zk-SNARK), a first cryptographic proof attesting that:
a first individual associated with the first user device was in a target proximity with a second individual associated with the second user device at a first time point; and
the first individual tested positive for a pathogen at a second time point within a threshold duration of the first time point;
transmitting, by the first user device, first publicly verifiable exposure data comprising at least the first cryptographic proof and the first hash to a public registry;
applying at least the first publicly verifiable exposure data, second publicly verifiable exposure data, and traffic data associated with movement of user devices within a geospatial region to a machine learning model, to obtain actionable intelligence associated with the pathogen;
generating a graph visualization corresponding to the traffic data; and
based at least on the actionable intelligence, determining one or more of:
a predicted future hotspot for the pathogen; and
a pathogen exposure risk of a user of the second user device.