Would we have any interest in standards-related discussion relative to
server log data anonymization?   See below for some new work starting up on
this topic in IETF.

Dave

David M. Oliver | david@g <[email protected]>uardianproject.info |
http://g <http://olivercoady.com>uardianproject.info | @davidmoliver | +1
970 368 2366


---------- Forwarded message ---------
From: Shivan Kaul Sahib <[email protected]>
Date: Mon, Nov 4, 2019 at 5:57 PM
Subject: [Pearg] Fwd: New Version Notification for draft-rao-pitfol-00.txt
To: <[email protected]>
Cc: <[email protected]>, <[email protected]>


Hi all,

Sandeep Rao from Grab, Ryan Guest from Salesforce and I have been
discussing log data classification shortly after Ryan's presentation on log
data privacy at the IETF 104 PEARG meeting. This draft is a first attempt
at exploring ways in which applications can tag log fields as containing
personal information for further anonymization/processing.

Sandeep will be presenting this draft at the upcoming IETF Singapore PEARG
meeting.

---------- Forwarded message ---------
From: <[email protected]>
Date: Mon, Nov 4, 2019 at 2:44 PM
Subject: New Version Notification for draft-rao-pitfol-00.txt
To: Ryan Guest <[email protected]>, Sandeep Rao <
[email protected]>, Shivan Sahib <[email protected]>



A new version of I-D, draft-rao-pitfol-00.txt
has been successfully submitted by Shivan Sahib and posted to the
IETF repository.

Name:           draft-rao-pitfol
Revision:       00
Title:          Personal Information Tagging for Logs (PITFoL)
Document date:  2019-11-04
Group:          Individual Submission
Pages:          6
URL:            https://www.ietf.org/internet-drafts/draft-rao-pitfol-00.txt
Status:         https://datatracker.ietf.org/doc/draft-rao-pitfol/
Htmlized:       https://tools.ietf.org/html/draft-rao-pitfol-00
Htmlized:       https://datatracker.ietf.org/doc/html/draft-rao-pitfol


Abstract:
   Software applications typically generate a large amount of log data
   in the course of their operation in order to help with monitoring,
   troubleshooting, etc.  However, like all data generated and operated
   upon by software systems, logs can contain information sensitive to
   users.  Personal data identification and anonymization in logs is
   thus crucial to ensure that no personal data is being inadvertently
   logged and retained which would make the logging application run
   afoul of laws around storing private information.  This document
   focuses on exploring mechanisms to specify personal or sensitive data
   in logs, to enable any server collecting, processing or analyzing
   logs to identify personal data and thereafter, potentially enforce
   any redaction.





Please note that it may take a couple of minutes from the time of submission
until the htmlized version and diff are available at tools.ietf.org.

The IETF Secretariat

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