June Change Proposal: text on de-identification

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I propose the following**for either a two state de-identification
regime, or "yellow" if we have three states.

Normative text:

Data can be considered de-identified if it has been deleted, modified,
aggregated, anonymized or otherwise manipulated in order to achieve a
reasonable level of justified confidence that the data cannot reasonably
be used to infer information about, or otherwise be linked to, a
particular user, user agent, or device.


Non-normative text:

Example 1. Hashing a pseudonym such as a cookie string does NOT provide
sufficient de-identification for an otherwise rich data set such as a
browsing history, since there are many ways to re-identify individuals
based on pseudonymous data.

Example 2. In many cases, keeping only high-level aggregate data, such
as the total number of visitors of a website each day broken down by
country (discarding data from countries without many visitors) would be
considered sufficiently de-identified.

Example 3. Deleting data is always a safe and easy way to achieve
de-identification.

Remark 1. De-identification is a property of data. If data can be
considered de-identified according to the “reasonable level of justified
confidence” clause of (1), then no data manipulation process needs to
take place in order to satisfy the requirements of (1).

Remark 2. There are a diversity of techniques being researched and
developed to de-identify data sets, and companies are encouraged to
explore and innovate new approaches to fit their needs.

Remark 3. It is a best practice for companies to perform “penetration
testing” by having an expert with access to the data attempt to
re-identify individuals or disclose attributes about them. The expert
need not actually identify or disclose the attribute of an individual,
but if the expert demonstrates how this could plausibly be achieved by
joining the data set against other public data sets or private data sets
accessible to the company, then the data set in question should no
longer be considered sufficiently de-identified and changes should be
made to provide stronger anonymization for the data set.*