<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.ietf-ppm-dap" target="https://datatracker.ietf.org/doc/html/draft-ietf-ppm-dap-17">
   <front>
      <title>Distributed Aggregation Protocol for Privacy Preserving Measurement</title>
      <author initials="T." surname="Geoghegan" fullname="Tim Geoghegan">
         <organization>ISRG</organization>
      </author>
      <author initials="C." surname="Patton" fullname="Christopher Patton">
         <organization>Cloudflare</organization>
      </author>
      <author initials="B." surname="Pitman" fullname="Brandon Pitman">
         <organization>ISRG</organization>
      </author>
      <author initials="E." surname="Rescorla" fullname="Eric Rescorla">
         <organization>Independent</organization>
      </author>
      <author initials="C. A." surname="Wood" fullname="Christopher A. Wood">
         <organization>Cloudflare</organization>
      </author>
      <date month="January" day="30" year="2026" />
      <abstract>
	 <t>   There are many situations in which it is desirable to take
   measurements of data which people consider sensitive.  In these
   cases, the entity taking the measurement is usually not interested in
   people&#x27;s individual responses but rather in aggregated data.
   Conventional methods require collecting individual responses and then
   aggregating them on some server, thus representing a threat to user
   privacy and rendering many such measurements difficult and
   impractical.  This document describes a multi-party Distributed
   Aggregation Protocol (DAP) for privacy preserving measurement which
   can be used to collect aggregate data without revealing any
   individual contributor&#x27;s data.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-ietf-ppm-dap-17" />
   
</reference>
