Amazon Technologies, Inc.

Keerat Singh Sharma

Pramod Raghavendran

Paul Anthony Kotas

Matthew Hamilton Battles

Chesley Bernard Coughlin

Guthrie Chipman Collin

Gerard Gjonej

Timothy John Craycroft

Anthony Crider

Joe Jony Jeyaratnam

Martin Christopher Hare Robertson

John Kenneth Fawcett

Rahul Chopra

Ankit Rajiv Kuwadekar

Hariharan Jayaraman

Maurice Lin

James Rupert William Phillips

Nicole Landis Ferragonio

Alan Kerry Lewis

A privacy protecting transaction engine for a cloud provider network is described. According to some embodiments, a computer-implemented method includes receiving a request from a customer of a cloud provider network to create a customer cloud in the cloud provider network, generating the customer cloud in the cloud provider network, receiving a first request at the cloud provider network for the customer cloud that includes private information of an end customer of the customer of the cloud provider network, removing the private information from the first request by a privacy protecting transaction engine of the cloud provider network to generate a second request, and sending the second request to the customer cloud for servicing.

Privacy protecting transaction engine for a cloud provider network

Devices, systems, and methods are provided for rotating cryptography secrets in data hashing. A method may include generating, based on a hashing technique, first obfuscated data using first data and a first version of a secret, and generating first metadata associated with the first obfuscated data, the first metadata indicative of the first version of the secret. The method may include determining a second version of the secret based on the first metadata. The method may include generating, based on the hashing technique, second obfuscated data using the first obfuscated data and the second version of the secret, and generating second metadata associated with the second obfuscated data, the second metadata indicative of the second version of the secret.

Enhanced secret rotation in data hashing

Data clean rooms provided for subscribers to advertising analysis services include data regarding advertising impressions, selections, view or conversion events, and memberships of audience segments, and computing functions or capacities for processing the data in an anonymized fashion. When advertisements are presented to customers, and interactions by customers (e.g., impressions, views, clicks, conversions or others) with goods or services are detected, data regarding the interactions may be aggregated and stored. When queries on behalf of an advertiser are identified, data associated with the queries may be retrieved and stored in a data clean room for processing or analysis. Anonymized responses to the query may be returned to the customer or serve as basis for one or more advertising events.

Advertising analysis using data clean rooms

Various approaches discussed herein enable techniques for managing privacy with respect to location-based operations, for example by receiving point of interest (POI) data corresponding to location data such as global positioning service (GPS) data at a computing device along with various location-based rules, which when satisfied, result in attribution events being generated that indicate various characteristics associated with POIs in the POI data. The attribution events are then sent to a server without compromising the location privacy of the computing device, because the location of the computing device is not included with the attribution events.

Maintaining privacy in location-based operations

Systems, methods, and computer-readable media are disclosed for automated sensitive information and data storage compliance verification. In one embodiment, an example method may include determining a software application stored at a database, determining software code of the software application, and determining that the software code includes a function that accesses critical user information. Example methods may include determining a risk score for the software application based at least in part on the function, and determining a compliance level for the software application based at least in part on the function.

Automated sensitive information and data storage compliance verification

Systems, methods, and computer-readable media are disclosed for detecting anomalous advertising content and taking or directing one or more actions to be taken to mitigate risk associated with anomalous advertising content. The anomalous advertising content indicates a deviation from an expected state of the advertising content. Various measures may be taken to determine whether the anomalous advertising content is reflective of malware.

Detection of anomalous advertising content

Growing community of inventors

Lynwood, WA, United States of America

Keerat Singh Sharma