Snap Inc.

Apoorvaa Deshpande

Amit Datta

Samarth Chopra

Bahador Yeganeh

Hooman Javaheri

Systems and methods herein describe privacy preserving multi-touch attribution. The described systems access a plurality of impression events and a plurality of conversion events, and for each impression event and each conversion event, wherein each impression event and each conversion event are associated with user identifiers, the described systems generates a hashed user identifier based on the associated user identifier, initiates a key agreement protocol comprising a key, generates an encrypted identifier by encrypting the hashed user identifier with the key, and stores the encrypted identifier.

Privacy-preserving multi-touch attribution

The technical problem of matching records in different datasets, for example a host dataset and a partner dataset storing records representing respective users, while maintaining the privacy of each dataset, is addressed by providing a privacy safe joint identification protocol. The privacy safe joint identification protocol computes respective anonymous joint identifiers for records in the two datasets. An anonymous joint identifier is generated such that the host-assigned and the partner-assigned identifies that have been determined to represent the same user are mapped to the same anonymous joint identifier.

Privacy safe joint identification protocol

An example computer-implemented system maintains user profiles and displays external content. Method and system are provided for performing attribution of conversions with respect to the external content in a privacy safe manner by anonymizing personally identifiable information utilizing cryptographic salt.

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Santa Monica, CA, United States of America

Apoorvaa Deshpande