| Network Working Group | I. Learmonth |
| Internet-Draft | Tor Project |
| Intended status: Informational | May 16, 2019 |
| Expires: November 17, 2019 |
Guidelines for Performing Safe Measurement on the Internet
draft-learmonth-pearg-safe-internet-measurement-02
Researchers from industry and academia will often use Internet measurements as a part of their work. While these measurements can give insight into the functioning and usage of the Internet, they can come at the cost of user privacy. This document describes guidelines for ensuring that such measurements can be carried out safely.
Comments are solicited and should be addressed to the research group's mailing list at pearg@irtf.org and/or the author(s).
The sources for this draft are at:
https://github.com/irl/draft-safe-internet-measurement
This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet-Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress."
This Internet-Draft will expire on November 17, 2019.
Copyright (c) 2019 IETF Trust and the persons identified as the document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (https://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document.
When performing research using the Internet, as opposed to an isolated testbed or simulation platform, means that you research co-exists in a space with other users. This document outlines guidelines for academic and industry researchers that might use the Internet as part of scientific experiementation.
Following the guidelines contained within this document is not a substitute for any institutional ethics review process you may have, although these guidelines could help to inform that process. Similarly, these guidelines are not legal advice and local laws must also be considered before starting any experiment that could have adverse impacts on user privacy.
Internet measurement studies can be broadly categorized into two groups: active measurements and passive measurements. Active measurements generate traffic. Performance measurements such as TCP throughput testing [RFC6349] or functional measurements such as the feature-dependent connectivity failure tests performed by [PATHspider] both fall into this category. Performing passive measurements requires existing traffic. Passive measurements can help to inform new developments in Internet protocols but can also carry risk.
The type of measurement is not truly binary and many studies will include both active and passive components. Each of the considerations in this document must be carefully considered for their applicability regardless of the type of measurement.
Ideally, informed consent would be collected from all users of a shared network before measurements were performed on them. In cases where it is practical to do so, this should be done.
For consent to be informed, all possible risks must be presented to the users. The considerations in this document can be used to provide a starting point although other risks may be present depending on the nature of the measurements to be performed.
In cases where it is not practical to collect informed consent from all users of a shared network, it may be possible to obtain proxy consent. Proxy consent may be given by a network operator or employer that would be more familiar with the expectations of users of a network than the researcher.
In larger scale measurements, even proxy consent collection may not be practical. In this case, implied consent may be presumed from users for some measurements. Consider that users of a network will have certain expectations of privacy and those expectations may not align with the privacy guarantees offered by the technologies they are using. As a thought experiment, consider how users might respond if you asked for their informed consent for the measurements you'd like to perform.
For example, the operator of a web server that is exposed to the Internet hosting a popular website would have the expectation that it may be included in surveys that look at supported protocols or extensions but would not expect that attempts be made to degrade the service with large numbers of simultaneous connections.
If practical, attempt to obtain informed consent or proxy consent from a sample of users to better understand the expectations of other users.
Wherever possible, use a testbed. An isolated network means that there are no other users sharing the infrastructure you are using for your experiments.
When measuring performance, competing traffic can have negative effects on the performance of your test traffic and so the testbed approach can also produce more accurate and repeatable results than experiments using the public Internet.
WAN link conditions can be emulated through artificial delays and/or packet loss using a tool like [netem]. Competing traffic can also be emulated using traffic generators.
When performing measurements be sure to only capture traffic that you have generated. Traffic may be identified by IP ranges or by some token that is unlikely to be used by other users.
Again, this can help to improve the accuracy and repeatability of your experiment. [RFC2544], for performance benchmarking, requires that any frames received that were not part of the test traffic are discarded and not counted in the results.
If your experiment is designed to trigger a response from infrastructure that is not your own, consider what the negative consequences of that may be. At the very least your experiment will consume bandwidth that may have to be paid for.
In more extreme circumstances, you could cause traffic to be generated that causes legal trouble for the owner of that infrastructure. The Internet is a global network crossing many legal jurisdictions and so what may be legal for you is not necessarily legal for everyone.
If you are sending a lot of traffic quickly, or otherwise generally deviate from typical client behaviour, a network may identify this as an attack which means that you will not be collecting results that are representative of what a typical client would see.
When performing active measurements on a shared network, maintain a list of hosts that you will never scan regardless of whether they appear in your target lists. When developing tools for performing active measurement, or traffic generation for use in a larger measurement system, ensure that the tool will support the use of a "Do Not Scan" list.
If complaints are made that request you do not generate traffic towards a host or network, you must add that host or network to your "Do Not Scan" list, even if no explanation is given or the request is automated.
You may ask the requester for their reasoning if it would be useful to your experiment. This can also be an oppertunity to explain your research and offer to share any results that may be of interest. If you plan to share the reasoning when publishing your measurement results, e.g. in an academic paper, you must seek consent for this from the requester.
Be aware that in publishing your measurement results, it may be possible to infer your "Do Not Scan" list from those results. For example, if you measured a well-known list of popular websites then it would be possible to correlate the results with that list to determine which are missing.
When deciding on the data to collect, assume that any data collected might become public. There are many ways that this could happen, through operation security mistakes or compulsion by a judicial system.
For all data collected, consider whether or not it is really needed.
When collecting data, consider if the granularity can be limited by using bins or adding noise. XXX: Differential privacy.
Do this at the source, definitely do it before you write to disk.
[Tor.2017-04-001] presents a case-study on the in-memory statistics in the software used by the Tor network, as an example.
The benefits should outweigh the risks. Consider auxiliary data (e.g. third-party data sets) when assessing the risks.
Take reasonable security precautions, e.g. about who has access to your data sets or experimental systems.
This document has no actions for IANA.
Many of these considerations are based on those from the [TorSafetyBoard] adapted and generalised to be applied to Internet research.
Other considerations are taken from the Menlo Report [MenloReport] and its companion document [MenloReportCompanion].