This is an in-depth technical explainer. If you're looking for a high-level introduction to Attribution Reporting with event-level reports, head over to Event-level reports in the Attribution Reporting API.

A list of all API guides and blog posts for this API is also available here.

Attribution Reporting with event-level reports

This document is an explainer for a potential new web platform feature which allows for measuring and reporting ad click and view conversions.

See the explainer on aggregate measurement for a potential extension on top of this.

Table of Contents

Motivation
Related work
API Overview
Privacy Considerations
Security considerations

Motivation

Currently, the web ad industry measures conversions via identifiers they can associate across sites. These identifiers tie information about which ads were clicked to information about activity on the advertiser's site (the conversion). This allows advertisers to measure ROI, and for the entire ads ecosystem to understand how well ads perform.

Since the ads industry today uses common identifiers across advertiser and publisher sites to track conversions, these common identifiers can be used to enable other forms of cross-site tracking.

This doesn’t have to be the case, though, especially in cases where identifiers such as third-party cookies are either unavailable or undesirable. A new API surface can be added to the web platform to satisfy this use case without them, in a way that provides better privacy to users.

This API alone will not be able to support all conversion measurement use cases. We envision this API as one of potentially many new APIs that will seek to reproduce valid advertising use cases in the web platform in a privacy preserving way. In particular, we think this API could be extended by using server side aggregation to provide richer data, which we are continuing to explore.

Related work

There is an alternative Private Click Measurement draft spec in the PrivacyCG. See this WebKit blog post for more details.

There are multiple aggregate designs in wicg/privacy-preserving-ads, including Bucketization and MaskedLARK.

Folks from Meta and Mozilla have published the Interoperable Private Attribution(IPA) proposal for doing aggregate attribution measurement.

Brave has published and implemented an Ads Confirmation Protocol.

API Overview

Registering attribution sources

Attribution sources are events which future triggers can be attributed to.

Sources are registered by returning a new HTTP response header on requests which are eligible for attribution. A request is eligible as long as it has the Attribution-Reporting-Eligible request header.

There are two types of attribution sources, navigation sources and event sources.

navigation sources are registered via clicks on anchor tags:

<a href="https://advertiser.example/landing"
   attributionsrc="https://adtech.example/attribution_source?my_ad_id=123">
   click me
</a>

or via calls to window.open that occur with transient activation:

// Encode the attributionsrc URL in case it contains special characters, such as '=', that will
// cause the parameter to be improperly parsed
const encoded = encodeURIComponent('https://adtech.example/attribution_source?my_ad_id=123');
window.open(
  "https://advertiser.example/landing",
  "_blank",
  `attributionsrc=${encoded}`);

event sources do not require any user interaction and can be registered via <img> or <script> tags with the new attributionsrc attribute:

<img src="https://advertiser.example/pixel"
     attributionsrc="https://adtech.example/attribution_source?my_ad_id=123">

<script src="https://advertiser.example/register-view"
        attributionsrc="https://adtech.example/attribution_source?my_ad_id=123">

Specifying a URL value for attributionsrc within <a>, <img>, <script> or window.open will cause the browser to initiate a separate keepalive fetch request which includes the Attribution-Reporting-Eligible request header.

When the attributionsrc attribute is present in these surfaces/APIs, both with and without a value, existing requests made via src/href attributes or window.open will now include the Attribution-Reporting-Eligible request header. Each of these requests will be able to register attribution sources.

event sources can also be registered using existing JavaScript request APIs by setting the Attribution-Reporting-Eligible header manually:

const headers = {
  'Attribution-Reporting-Eligible': 'event-source'
};
// Optionally set keepalive to ensure the request outlives the page.
window.fetch("https://adtech.example/attribution_source?my_ad_id=123",
             { headers, keepalive: true });

Other requests APIs which allow specifying headers (e.g. XMLHttpRequest) will also work.

The response to these requests will configure the API via a new JSON HTTP header Attribution-Reporting-Register-Source of the form:

{
  "source_event_id": "12340873456",
  "destination": "[eTLD+1]",
  "expiry": "[64-bit signed integer]",
  "priority": "[64-bit signed integer]"
}

destination: an origin whose eTLD+1 is where attribution will be triggered for this source.
source_event_id: (optional) A string encoding a 64-bit unsigned integer which represents the event-level data associated with this source. This will be limited to 64 bits of information but the value can vary. Defaults to 0.
expiry: (optional) expiry in seconds for when the source should be deleted. Default is 30 days, with a maximum value of 30 days. The maximum expiry can also vary between browsers. This will be rounded to the nearest day.
priority: (optional) a signed 64-bit integer used to prioritize this source with respect to other matching sources. When a trigger redirect is received, the browser will find the matching source with highest priority value and generate a report. The other sources will not generate reports.

Once this header is received, the browser will proceed with handling an attribution source event. Note that it is possible to register multiple sources for the same request using HTTP redirects (though these multiple sources may not set distinct destinations).

Note that we sometimes call the attributionsrc's origin the "reporting origin" since it is the origin that will end up receiving attribution reports.

Handling an attribution source event

A navigation attribution source event will be logged to storage if the resulting document being navigated to ends up sharing an eTLD+1 with the destination origin. Additionally, the navigation needs occur with transient user activation.

event sources don’t require any of the above constraints to be logged.

An attribution source will be eligible for reporting if any page on the destination eTLD+1 (advertiser site) triggers attribution for the associated reporting origin.

Publisher-side Controls for Attribution Source Declaration

In order to prevent arbitrary third parties from registering sources without the publisher’s knowledge, the Attribution Reporting API will need to be enabled in child contexts by a new Permissions Policy:

<iframe src="https://advertiser.example" allow="attribution-reporting 'src'">

<a … attributionsrc="https://ad-tech.example?..."></a>

</iframe>

The API will be enabled by default in the top-level context and in same-origin children. Any script running in these contexts can declare a source with any reporting origin. Publishers who wish to explicitly disable the API for all parties can do so via an HTTP header.

Without a Permissions Policy, a top-level document and cooperating iframe could recreate this functionality. This is possible by using postMessage to send the source_event_id, attributionsrc origin, destination values to the top level document who can then wrap the iframe in an anchor tag (with some additional complexities behind handling clicks on the iframe). Using Permissions Policy prevents the need for these hacks. This is inline with the classification of powerful features as discussed on this issue.

NOTE: For the Chromium Origin Trial, the Chromium implementation of the Attribution Reporting API will temporarily ship with a Permissions Policy default of *, which bypasses the need for top-level documents to delegate permission to cross-origin iframes.

Triggering Attribution

Attribution can only be triggered for a source on a page whose eTLD+1 matches the eTLD+1 of the site provided in destination. To trigger attribution, a similar mechanism is used as source event registration, via HTML:

<img src="https://ad-tech.example/conversionpixel"
     attributionsrc="https://adtech.example/attribution_trigger?purchase=13">

or JavaScript:

const headers = {
  'Attribution-Reporting-Eligible': 'trigger'
};
// Optionally set keepalive to ensure the request outlives the page.
window.fetch("https://adtech.example/attribution_trigger?purchase=13",
             { headers, keepalive: true });

As a stop-gap to support pre-existing conversion tags which do not include the attributionsrc attribute, or use a different Fetch API, the browser will also process trigger registration headers for all subresource requests on the page where the attribution-reporting Permissions Policy is enabled.

Like source event registrations, these requests should respond with a new HTTP header Attribution-Reporting-Register-Trigger which contains information about how to treat the trigger event:

{
  "event_trigger_data": [{
    "trigger_data": "[unsigned 64-bit integer]",
    "priority": "[signed 64-bit integer]",
    "deduplication_key": "[unsigned 64-bit integer]"
  }]
}

trigger_data: optional coarse-grained data to identify the triggering event. The value will be limited to either 3 bits or 1 bit depending on the attributed source type.
priority: optional signed 64-bit integer representing the priority of this trigger compared to other triggers for the same source.
deduplication_key: optional unsigned 64-bit integer which will be used to deduplicate multiple triggers which contain the same deduplication_key for a single source.

When this header is received, the browser will schedule an attribution report as detailed in Trigger attribution algorithm. Note that the header can be present on redirect requests.

Triggering attribution requires the attribution-reporting Permissions Policy to be enabled in the context the request is made. As described in Publisher Controls for Attribution Source Declaration, this Permissions Policy will be enabled by default in the top-level context and in same-origin children, but disabled in cross-origin children.

Navigation sources may be attributed up to 3 times. Event sources may be attributed up to 1 time.

Registration requests

Depending on the context in which it was made, a request is eligible to register sources, triggers, sources or triggers, or nothing, as indicated in the Attribution-Reporting-Eligible request header, which is a structured dictionary.

The reporting origin may use the value of this header to determine which registrations, if any, to include in its response. The browser will likewise ignore invalid registrations:

<a> and window.open will have navigation-source.
Other APIs that automatically set Attribution-Reporting-Eligible (like <img>) will contain event-source, trigger.
Requests from JavaScript, e.g. window.fetch, can set this header manually, but it is an error for such requests to specify navigation-source.
All other requests will not have the Attribution-Reporting-Eligible header. For those requests the browser will permit trigger registration only.

Data limits and noise

The source_event_id will be limited to 64 bits of information to enable uniquely identifying an ad click.

The advertiser-side data must therefore be limited quite strictly, by limiting the amount of data and by applying noise to the data. navigation sources will be limited to only 3 bits of trigger_data, while event sources will be limited to only 1 bit.

Noise will be applied to whether a source event will be reported truthfully. When an attribution source is registered, the browser will perform one of the following steps given a probability p:

With probability 1 - p, the browser logs the source as normal
With probability p, the browser chooses randomly among all the possible output states of the API. This includes the choice of not reporting anything at all, or potentially reporting multiple fake reports for the event.

Note that this scheme is an instantiation of k-randomized response, see Differential privacy.

Strawman: we can set p such that each source is protected with randomized response that satisfies an epsilon value of 14. This would entail:

p = .24% for navigation sources
p = .00025% for event sources

Note that correcting for this noise addition is straightforward in most cases, please see <TODO link to de-biasing advice/code snippet here>. Reports will be updated to include p so that noise correction can work correctly in the event that p changes over time, or if different browsers apply different probabilities:

{
  "randomized_trigger_rate": 0.0024,
  ...
}

Note that these initial strawman parameters were chosen as a way to ease adoption of the API without negatively impacting utility substantially. They are subject to change in the future with additional feedback and do not necessarily reflect a final set of parameters.

Trigger attribution algorithm

When the browser receives an attribution trigger redirect on a URL matching the destination eTLD+1, it looks up all sources in storage that match <attributionsrc origin, destination> and picks the one with the greatest priority. If multiple sources have the greatest priority, the browser picks the one that was stored most recently.

The browser then schedules a report for the source that was picked by storing {attributionsrc origin, destination eTLD+1, source_event_id, decoded trigger_data, priority, deduplication_key} for the source. Scheduled reports will be sent as detailed in Sending scheduled reports.

The browser will create reports for a source only if the trigger's deduplication_key has not already been associated with a report for that source.

Each navigation source is allowed to schedule only a maximum of three reports, while each event source is only allowed to schedule a maximum of one.

If a source has already scheduled the maximum number of reports when a new report is being scheduled, the browser will compare the priority of the new report with the priorities of the scheduled reports for that source. If the new report has the lowest priority, it will be ignored. Otherwise, the browser will delete the scheduled report with the lowest priority and schedule the new report.

Multiple sources for the same trigger (Multi-touch)

If multiple sources were registered and associated with a single attribution trigger, send reports for the one with the highest priority. If no priority is specified, the browser performs last-touch.

There are many possible alternatives to this, like providing a choice of rules-based attribution models. However, it isn’t clear the benefits outweigh the additional complexity. Additionally, models other than last-click potentially leak more cross-site information if sources are clicked across different sites.

Sending Scheduled Reports

Reports for event sources will be sent 1 hour after the source expires at its expiry.

Reports for navigation sources may be reported earlier than the source's expiry, at specified points in time relative to when the source event was registered. See here for the precise algorithm.

Note that the report may be sent at a later date if the browser was not running when the window finished. In this case, reports will be sent on startup. The browser may also decide to delay some of these reports for a short random time on startup, so that they cannot be joined together easily by a given reporting origin.

Attribution Reports

To send a report, the browser will make a non-credentialed (i.e. without session cookies) secure HTTP POST request to:

https://<reporting origin>/.well-known/attribution-reporting/report-event-attribution

The report data is included in the request body as a JSON object with the following keys:

attribution_destination: the attribution destination set on the source
source_event_id: 64-bit event id set on the attribution source
trigger_data: Coarse data set in the attribution trigger registration
report_id: A UUID string for this report which can be used to prevent double counting
source_type: Either "navigation" or "event", indicates whether this source was associated with a navigation.
randomized_trigger_rate: Decimal number between 0 and 1 indicating how often noise is applied.

Data Encoding

The source event id and trigger data should be specified in a way that is amenable to the privacy assurances a browser wants to provide (i.e. the number of distinct data states supported).

The input values will be 64-bit integers which the browser will interpret modulo its maximum data value chosen by the browser. The browser will take the input and performs the equivalent of:

function getData(input, max_value) {
  return input % max_value;
}

The benefit of this method over using a fixed bit mask is that it allows browsers to implement max_values that aren’t multiples of 2. That is, browers can choose a "fractional" bit limit if they want to.

Optional attribution filters

Source and trigger registration has additional optional functionality to both:

Selectively filter some triggers (effectively ignoring them)
Choose trigger data based on source event data

This can be done via simple extensions to the registration configuration.

Source registration:

{
  "source_event_id": "12345678",
  "destination": "https://toasters.example",
  "expiry": "604800000",
  "filter_data": {
    "conversion_subdomain": ["electronics.megastore", "electronics2.megastore"],
    "product": ["1234"]
    // Note that "source_type" will be automatically generated as
    // one of {"navigation", "event"}
  }
}

Trigger registration:

{
  ... // existing fields, such as `event_trigger_data`

  // Note that "not_filters", which filters with a negation, is also supported.
  "filters": {
    "conversion_subdomain": ["electronics.megastore"],
    // Not set on the source side, so this key is ignored
    "directory": ["/store/electronics]"
  }
}

If keys in the filters JSON match keys in filter_data, the trigger is completely ignored if the intersection is empty.

Note: A key which is present in one JSON and not the other will not be included in the matching logic.

Note: The filter JSON does not support nested dictionaries or lists. filter_data and filters are only allowed to have a list of values with string type.

The event_trigger_data field can also be extended to do selective filtering to set trigger_data based on filter_data:

// Filter by the source type to handle different bit limits.
{
  "event_trigger_data": [
    {
      "trigger_data": "2",
      // Note that "not_filters", which filters with a negation, is also supported.
      "filters": {"source_type": ["navigation"]}
    },
    {
      "trigger_data": "1",
      "filters": {"source_type": ["event"]}
    }
  ]
}

If the filters do not match for any of the event triggers, no event-level report will be created.

If the filters match for multiple event triggers, the first matching event trigger is used.

Optional: extended debugging reports

The Attribution Reporting API is a new and fairly complex way to do attribution measurement without third-party cookies. As such, we are open to introducing a transitional mechanism to learn more information about attribution reports while third-party cookies are available. This ensures that the API can be fully understood during roll-out and help flush out any bugs (either in browser or caller code), and more easily compare the performance to cookie-based alternatives.

Source and trigger registrations will both accept a new field debug_key:

{
  ...
  "debug_key": "[64-bit unsigned integer]"
}

Reports will include up to two new parameters which pass any specified debug keys from source and trigger events unaltered:

{
  // normal report fields...
  "source_debug_key": "[64-bit unsigned integer]",
  "trigger_debug_key": "[64-bit unsigned integer]"
}

If a report is created with both source and trigger debug keys, a duplicate debug report will be sent immediately to a .well-known/attribution-reporting/debug/report-event-attribution endpoint. The debug reports will be identical to normal reports, including the two debug key fields. Including these keys in both allows tying normal reports to the separate stream of debug reports.

Note that event-level reports associated with false trigger events will not have trigger_debug_keys. This allows developers to more closely understand how noise is applied in the API.

To ensure that this data (which could enable cross-site tracking) is only available in a transitional phase while third-party cookies are available and are already capable of user tracking, the browser will check (at both source and trigger registration) for the presence of a special SameSite=None cookie set by the reporting origin:

Set-Cookie: ar_debug=1; SameSite=None; Secure; HttpOnly

If a cookie of this form is not present, debugging information will be ignored.

Note that in the context of proposals such as CHIPS, the cookie must be unpartitioned in order to allow debug keys to be registered.

Sample Usage

publisher.example wants to show ads on their site, so they contract out to ad-tech.example. ad-tech.example's script in the main document creates a cross-origin iframe to host the third party advertisement for toasters.example.

Within the iframe, ad-tech-3p.example code annotates their anchor tags to use the ad-tech.example reporting origin, and sets the attributionsrc attribute based on the ad that was served (e.g. some ad with id 123456).

<iframe src="https://ad-tech-3p.example/show-some-ad"
        allow="attribution-reporting">
...
<a
  href="https://toasters.example/purchase"
  attributionsrc="https://ad-tech.example?adid=123456">
  click me!
</a>
...
</iframe>

A user clicks on the ad and this opens a window that lands on a URL to toasters.example/purchase. In the background, the browser issues an HTTP request to https://ad-tech.example?adid=123456. The ad-tech responds with a Attribution-Reporting-Register-Source JSON header:

{
  "source_event_id": "12345678",
  "destination": "https://toasters.example",
  "expiry": "604800000"
}

2 days later, the user buys something on toasters.example. toasters.example triggers attribution on the few different ad-tech companies it buys ads on, including ad-tech.example, by adding conversion pixels:

<img src="..." attributionsrc="https://ad-tech.example/trigger-attribution?model=toastmaster3000&price=$49.99&...">

ad-tech.example receives this request, and decides to trigger attribution on toasters.example. They must compress all of the data into 3 bits, so ad-tech.example chooses to encode the value as "2" (e.g. some bucketed version of the purchase value). They respond to the request with an Attribution-Reporting-Register-Trigger header:

{
  "event_trigger_data": [{
    "trigger_data": "2"
  }]
}

The browser sees this response, and schedules a report to be sent. The report is associated with the 7-day deadline as the 2-day deadline has passed. Roughly 5 days later, ad-tech.example receives the following HTTP POST to https://ad-tech.example/.well-known/attribution-reporting/report-event-attribution with the following body:

{
  "attribution_destination": "https://toasters.example",
  "source_event_id": "12345678",
  "trigger_data": "2"
}

Noisy fake conversion example

Assume the caller uses the same inputs as in the above example, however, the noise mechanism in the browser chooses to generate completely fake data for the source event. This occurs with some probability p.

To generate fake events, the browser considers all possible outputs for a given source event:

No reports at all
One report with metadata "0" at the first reporting window
One report with metadata "1" at the first reporting window and one report with metadata "3" at the second reporting window
etc. etc. etc.

After enumerating all possible outputs of the API for a given source event, the browser simply selects one of them at random uniformly. Any subsequent true trigger events that would be attributed to the source event are completely ignored.

In the above example, the browser could have chosen to generate three reports:

One report with metadata "7", sent 2 days after the click
One report with metadata "3", sent 7 days after the click
One report with metadata "0", also sent 7 days after the click

Storage limits

The browser may apply storage limits in order to prevent excessive resource usage.

Strawman: There should be a limit of 1024 pending sources per source origin.

Strawman: There should be a limit of 1024 pending event-level reports per destination site.

Privacy Considerations

A primary privacy goal of the API is to make linking identity between two different top-level sites difficult. This happens when either a request or a JavaScript environment has two user IDs from two different sites simultaneously.

Secondary goals of the API are to:

give some level of plausible deniability to cross-site data leakage associated with source events.
limit the raw amount of cross-site information a site can learn relative to a source event

In this API, the 64-bit source ID can encode a user ID from the publisher’s top- level site, but the low-entropy, noisy trigger data could only encode a small part of a user ID from the advertiser’s top-level site. The source ID and the trigger data are never exposed to a JavaScript environment together, and the request that includes both of them is sent without credentials and at a different time from either event, so the request adds little new information linkable to these events. This allows us to limit the information gained by the ad-tech relative to a source event.

Additionally, there is a small chance that all the output for a given source event is completely fabricated by the browser, giving the user plausible deniability whether subsequent trigger events actually occurred the way they were reported.

Trigger Data

Trigger data, e.g. advertiser-side data, is extremely important for critical use cases like reporting the purchase value of a conversion. However, too much advertiser-side data could be used to link advertiser identity with publisher identity.

Mitigations against this are to provide only coarse information (only a few bits at a time), and introduce some noise to the API output. Even sophisticated attackers will therefore need to invoke the API multiple times (through multiple clicks/views) to join identity between sites with high confidence.

Note that this noise still allows for aggregate measurement of bucket sizes with an unbiased estimator (assuming rate-limits are not hit) See generic approaches of dealing with Randomized response for a starting point.

TODO: Update this script to account for the more complicated randomized response approach.

Reporting Delay

By bucketing reports within a small number reporting deadlines, it becomes harder to associate a report with the identity of the user on the advertiser’s site via timing side channels.

Reports within the same reporting window occur within an anonymity set with all others during that time period. For example, if we didn’t bucket reports with a delay (and instead sent them immediately after a trigger event), the reports (which contain publisher IDs) could be easily joined up with the advertiser’s first-party information via correlating timestamps.

Note that the delay windows / deadlines chosen represent a trade-off with utility, since it becomes harder to properly assign credit to a click if the time from click to conversion is not known. That is, time-to-conversion is an important signal for proper attribution. Browsers should make sure that this trade-off is concretely evaluated for both privacy and utility before deciding on a delay.

Reporting origin limits

If the advertiser is allowed to cycle through many possible reporting origins, then the publisher and advertiser don’t necessarily have to agree apriori on what origin to use, and which origin actually ends up getting used reveals some extra information.

To prevent this kind of abuse, the browser should limit the number of reporting origins per <source site, destination site> pair, counted per source registration. This should be limited to 100 origins per 30 days.

Additionally, there should be a limit of 10 reporting origins per <source site, destination site, 30 days>, counted for every attribution that is generated.

Clearing Site Data

Attribution source data and attribution reports in browser storage should be clearable using existing "clear browsing data" functionality offered by browsers.

Reporting cooldown / rate limits

To limit the amount of user identity leakage between a <source site, destination> pair, the browser should throttle the amount of total information sent through this API in a given time period for a user. The browser should set a maximum number of attributions per

tuple per time period. If this threshold is hit, the browser will stop scheduling reports the API for the rest of the time period for attributions matching that tuple.

The longer the cooldown windows are, the harder it is to abuse the API and join identity. Ideally attribution thresholds should be low enough to avoid leaking too much information, with cooldown windows as long as practically possible.

Note that splitting these limits by the reporting origin introduces a possible leak when multiple origins collude with each other. However, the alternative makes it very difficult to adopt the API if all reporting origins had to share a budget.

Strawman rate limit: 100 attributions per {source site, destination, reporting origin, 30 days}

Less trigger-side data

Registering event attribution sources is not gated on a user interaction or top- level navigation, allowing them to be registered more frequently and with greater ease. For example, by restricting to 1 bit of data and 1 report per event source, a reportingorigin would need to register many more sources in order to link cross-site identity relative to the Click Through API.

This is further restricted by rate-limiting the usage of the API between two sites, using reporting cooldowns. Due to the different characteristics between classes of sources, these cooldowns should have independent limits on the number of reports of each type.

The number of reporting windows is another vector which can contain trigger-side information. By restricting to a single window, a reportingorigin does not receive any additional information on when in the attribution window a source was triggered.

Browsing history reconstruction

Reporting attribution without a pre-existing navigation allows the reportingorigin to learn whether a given user on the source site visited the destination site at all. For click-through reports, this is not an issue because the reportingorigin knows a priori the user was navigating to destination.

This new threat is be mitigated in a number of ways:

Adding noise to whether a trigger is genuine

By adding noise to whether an attribute source gets triggered, a reporting origin will not know with absolute certainty whether a particular ad view led to a site visit. See Differential privacy.

Limiting the number of unique destinations covered by pending sources

To limit the breadth of destination sites that a reporting origin may be trying to measure user visits on, the browser can limit the number destination eTLD+1s represented by pending sources for a source-site.

The browser can place a limit on the number of a source site's pending source's unique destinations. When an attribution source is registered for an eTLD+1 that is not already in the pending sources and a source site is at its limit, the browser will drop the new source.

The lower this value, the harder it is for a reporting origin to use the API to try and measure user browsing activity not associated with ads being shown. Browsers may choose parameters on the number of destinations to make their own tradeoffs for privacy and utility.

Because this limit is per source site, it is possible for different reporting origin on a site to push the other attribution sources out of the browser. See the denial of service for more details. To prevent this attack, the browser should maintain these limits per reporting origin. This effectively limits the number of unique sites covered by pending sources from any one reporting origin.

Strawman: 100 distinct destination sites per-{source site, reporting origin}, applied to all pending sources regardless of type.

TODO: should this be applied over a time period?

Differential privacy

A goal of this work is to create a framework that would support making event-level measurement that satisfies local differential privacy. This follows from our use of k-randomized response to generate noisy output for each source event. For a given output space O with cardinality k, true value v in the output space, and flip probability p, the k-randomized response algorithm:

Flips a biased coin with heads probability p
If heads, return a random value in O
Otherwise return v

k-randomized response is an algorithm that is epsilon differentially private if p = k / (k + exp(epsilon) - 1). For low enough values of epsilon, a given source’s true output should be well protected by the randomized response mechanism.

Note that the number of all possible output states k in the above design is:

2925 for click sources. This results from a particular "stars and bars" counting method which derives k = (num_reporting_windows * num_trigger_data + num_reports choose num_reports) = (3 * 8 + 3 choose 3). TODO: outline why this is the case.
3 for event-sources (no attribution, attribution with trigger data 1, attribution with trigger data 0). This also follows from (1 * 2 + 1 choose 1).

Note that the scope of privacy in the current design is not user-level, but rather source-level. This follows from the fact that noise is added independently per source-event, and source events are not strictly rate-limited. Exact noise parameters are subject to change with feedback. The primary goal with this proposal as written is to ensure that the browser has the appropriate infrastructure foundation to develop locally differentially private methods in the future. Tightening the privacy scope will also be considered in future work.

Our plan is to adjust the level of noise added based on feedback during the origin trial period, and our goal with this initial version is to create a foundation for further exploration into formally private methods for measurement.

Speculative: Limits based on first party storage

Another mitigation on joining identity across publisher and advertiser sites is to limit the number of reports for any given <publisher, advertiser> pair until the advertiser clears their site data. This could occur via the Clear-Site-Data header or by explicit user action.

To prevent linking across deletions, we might need to introduce new options to the Clear-Site-Data header to only clear data after the page has unloaded.

Security considerations

Reporting origin control

Reports can only be generated if the same origin responds with headers that register source events and trigger events. There is no way for an origin to register events on behalf of another origin, which is an important restriction to prevent fraudulent reports.

Denial of service

Rate limits and other restrictions to the API can cause reports to no longer be sent in some cases. It is important to consider all the cases where an origin could utilize the API in some way to lock out other origins, and minimize that risk if possible.

Currently, the only known limit in this proposal that could risk denial of service is the reporting origin limits. This is an explicit trade-off for privacy that should be monitored for abuse.

Top site permission model

The Permissions Policy is used to globally enable or disable the API. Additionally, network requests need fine grained permission in the form of requiring an attributionsrc attribute.

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EVENT.md

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