Snap Inc.

Amit Datta

Subhash Sankuratripati

Masoud Akhoondi

Apoorvaa Deshpande

Ioannis Kotsogiannis Teftsoglou

Samarth Chopra

Dhanuja Shaji

Liviu Cristea

Vasyl Pihur

Balamurugan Anandan

Aleksandra Korolova

Hooman Javaheri

Bahador Yeganeh

When a messaging system generates connection recommendations for a new user, who first registers with the messaging system, the signals available for generation of recommendations may be limited to the user's contact book matches. Using just this limited signal poses a concern associated with leaking information about users represented by the recommendations. The technical problem of generating connection recommendations for a user at registration time in a privacy-safe manner is addressed by a recommendation methodology that obscures the connection source and the connection distance of the recommended profiles.

Privacy-safe connection recommendations

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

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.

Privacy safe anonymized identity matching

Disclosed are methods and systems for generating a suggestion inventory that provides improved user engagement while ensuring privacy of relationships on a social network. The methods and systems include accessing an entity graph that specifies connections between a plurality of users on the social network; identifying a first candidate user of the plurality of users that is indirectly connected to a given user of the plurality of users; computing a number of unique paths on the entity graph between the first candidate user and the given user; determining that the number of unique paths exceeds a first threshold and includes a minimum number of friends of the given user that are directly connected to the given user on the entity graph; and adding the first candidate friend to a friend suggestion inventory for the given user in response to the determination.

Generating a suggestion inventory

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for determining whether data utilization is privacy compliant. The program and method includes receiving input, via a graphical user interface, that includes identification of an application feature that utilizes user data collected from a plurality of users of the application; generating, for display in the graphical user interface, a plurality of fields that characterize utilization of user data; receiving, via the graphical user interface, a selection of one or more fields, the selected one or more fields characterize the utilization of the user data by the application feature; determining, based on the selected one or more fields, whether the utilization of the user data is privacy compliant; and generating, for display, an approval status indicating whether the utilization of the user data is privacy compliant.

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Los Angeles, CA, United States of America

Amit Datta