Internet DRAFT - draft-iab-m-ten-workshop
draft-iab-m-ten-workshop
Network Working Group M. Knodel
Internet-Draft Center for Democracy & Technology
Intended status: Informational W. Hardaker
Expires: 27 August 2023
T. Pauly
23 February 2023
Report from the IAB workshop on Management Techniques in Encrypted
Networks (M-TEN)
draft-iab-m-ten-workshop-00
Abstract
The “Management Techniques in Encrypted Networks (M-TEN)” workshop
was convened by the Internet Architecture Board (IAB) from 17 October
2022 to 19 October 2022 as a three-day online meeting. The workshop
was organized in three parts to discuss ways to improve network
management techniques in support of even broader adoption of
encryption on the Internet. This report summarizes the workshop's
discussion and identifies topics that warrant future work and
consideration.
Note that this document is a report on the proceedings of the
workshop. The views and positions documented in this report are
those of the workshop participants and do not necessarily reflect IAB
views and positions.
About This Document
This note is to be removed before publishing as an RFC.
The latest revision of this draft can be found at
https://intarchboard.github.io/m-ten-workshop-public/draft-iab-m-ten-
workshop.html. Status information for this document may be found at
https://datatracker.ietf.org/doc/draft-iab-m-ten-workshop/.
Source for this draft and an issue tracker can be found at
https://github.com/intarchboard/m-ten-workshop-public.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Workshop Scope and Discussion . . . . . . . . . . . . . . . . 4
2.1. "Where we are" - Requirements and Passive Observations . 4
2.1.1. Traffic classification and network management . . . . 4
2.1.2. Preventing traffic analysis . . . . . . . . . . . . . 5
2.1.3. Users and privacy . . . . . . . . . . . . . . . . . . 6
2.1.4. Discussion . . . . . . . . . . . . . . . . . . . . . 6
2.2. "Where we want to go" - Collaboration Principles . . . . 7
2.2.1. First party collaboration for network management . . 7
2.2.2. Second and third party collaboration for network
management . . . . . . . . . . . . . . . . . . . . . 8
2.2.3. Visible, optional network management . . . . . . . . 9
2.2.4. Discussion . . . . . . . . . . . . . . . . . . . . . 9
2.3. "How we get there" - Collaboration Use cases . . . . . . 10
2.3.1. Establishing expected contracts to enable security
management . . . . . . . . . . . . . . . . . . . . . 10
2.3.2. Zero Knowledge Middleboxes . . . . . . . . . . . . . 11
2.3.3. Red Rover - A collaborative approach to content
filtering . . . . . . . . . . . . . . . . . . . . . . 12
3. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 12
4. Informative References . . . . . . . . . . . . . . . . . . . 13
Appendix A. Position Papers . . . . . . . . . . . . . . . . . . 15
A.1. Motivations and principles . . . . . . . . . . . . . . . 15
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A.2. Classification and identification of encrypted traffic . 15
A.3. Ideas for collaboration and coordination between devices
and networks . . . . . . . . . . . . . . . . . . . . . . 15
A.4. Other background material . . . . . . . . . . . . . . . . 16
Appendix B. Workshop participants . . . . . . . . . . . . . . . 16
Appendix C. Program Committee . . . . . . . . . . . . . . . . . 16
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16
1. Introduction
User privacy and security are constantly being improved by
increasingly strong and more widely deployed encryption. This
workshop aims to discuss ways to improve network management
techniques in support of even broader adoption of encryption on the
Internet.
Network management techniques need to evolve to work effectively and
reliably in the presence of ubiquitous traffic encryption and support
techniques that enhance user privacy. In an all-encrypted network,
it is not viable to rely on unencrypted metadata for network
monitoring and security functions, troubleshooting devices, and
passive traffic measurements. New approaches are needed to track
network behaviors, e.g., by directly cooperating with endpoints and
applications, increasing use of in-band telemetry, increasing use of
active measurement approaches, and privacy-preserving inference
techniques.
The aim of this IAB online workshop from October 17-19, 2022, has
been to provide a platform to explore the interaction between network
management and traffic encryption and initiate new work on
collaborative approaches that promote security and user privacy while
supporting operational requirements. As such the workshop addressed
the following questions:
* What are actionable network management requirements?
* Who is willing to work on collaborative solutions?
* What are the starting points for collaborative solutions?
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2. Workshop Scope and Discussion
The workshop was organized across three, all-group discussion slots,
one per day. The following topic areas were identified and the
program committee organized paper submissions into three main themes
for each of the three discussion slots. During each discussion,
those papers were presented sequentially with open discussion held at
the end of each day.
2.1. "Where we are" - Requirements and Passive Observations
The first day of the workshop agenda focused on the existing state of
the relationship between network management and encrypted traffic
from various angles. Presentations ranged from discussing
classifiers using machine-learning to recognize traffic, to advanced
techniques for evading traffic analysis, to user privacy
considerations.
After an introduction that covered the goals of the workshop and the
starting questions (as described in Section 1), there were four
presentations, followed by open discussion.
2.1.1. Traffic classification and network management
Many existing network management techiques are passive in nature:
they don't rely on an explicit signals from end hosts to negotiate
with network middleboxes, but instead rely on inspecting packets to
recognize traffic and apply various policies. Traffic
classification, as a passive technique, is being challenged by
increasing encryption.
Traffic classification is commonly performed by networks to infer
what applications and services are being used. This information is
in turn used for capacity and resource planning, Quality-of-Service
(QoS) monitoring, traffic prioritization, network access control,
identity management, and malware detection. However, since
classification traditionally relies on recognizing unencrypted
properties of packets in a flow, increasing encryption of traffic can
decrease the effectiveness of classification.
The amount of classification that can be performed on traffic also
provides a useful insight onto how "leaky" the protocols used by
applications are, and points to areas where information is visible to
any observer, which may be malicious or not.
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Traditionally, classification has been based on experts crafting
specific rules, but there is also a move toward using maching
learning to recognize patterns. "Deep learning" machine learning
models generally rely on analyzing a large set of traffic over time,
and have trouble reacting quickly to changes in traffic patterns.
Models that are based on closed-world data sets also become less
useful over time, as traffic changes. [JIANG] describes experiments
that showed that a model that performs with high accuracy on an
initial data set became severely degraded when running on a newer
data set that contained traffic from the same applications. Even in
as little time as one week, the traffic classification would become
degraded. However, the set of features in packets and flows that
were useful for models stayed mostly consistent, even if the models
themselves needed to be updated. Models where the feature space is
reduced to fewer features showed better resiliency, and could be
retrained more quickly. Based on this, [JIANG] recommends more work
and research on determining which set of features in IP packets are
most useful for focused machine learning analysis. [WU] also
recommends further research investment in Artificial Intelligent (AI)
analysis for network management.
2.1.2. Preventing traffic analysis
Just as traffic classification is continually adapting, techniques to
prevent traffic analysis and obfuscate application and user traffic
are continually evolving. An invited talk from the authors of
[DITTO] shared a novel approach with the workshop for how to build a
very robust system to prevent unwanted traffic analysis.
Usually traffic obfuscation is performed by changing the timing of
packets or adding padding data. The practices can be costly and
negatively impact performance. DITTO demonstrated the feasibility of
applying traffic obfuscation on aggregated traffic in the network
with minimal overhead and in line speed.
While traffic obfuscation techniques are today not widely deployed,
this study underlines, together with the need for continuous effort
to keep traffic models updated over time, the challenges of
classification of encrypted traffic as well as opportunities to
further enhance user privacy.
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2.1.3. Users and privacy
The Privacy Enhancements and Assessments Research Group is working on
a document to discuss guidelines for how to measure traffic on the
Internet in a safe and privacy-friendly way
([I-D.irtf-pearg-safe-internet-measurement]). These guidelines and
principles provide another angle onto the discussion of passive
classification and analysis of traffic.
Consent for collection and measurement of metadata is an important
consideration in deploying network measurement techniques. This
consent can be explicitly given as informed consent, or can be given
by proxy or be only implied. For example, a user of a network might
need to consent to certain measurement and traffic treatment when
joining a network.
Various techniques for data collection can also improve user privacy,
such as discarding data after a short period of time, masking out
aspects of data that contain user-identifying information, reducing
the accuracy of collected data, and aggregating data.
2.1.4. Discussion
The intents and goals of users, application developers, and network
operators align in some cases, but not others. One of the recurring
challenges that came up was not having a clear way to understand or
communicate intents and requirements. Both traffic classification
and traffic obfuscation attempt to change the visibility of traffic
without cooperation of other parties: traffic classification is a
network attempting to inspect application traffic without
coordination from applications, and traffic obfuscation is an attempt
to hide that same traffic as it transits a network.
Traffic adaptation and prioritization is one dimension in which the
incentives for cooperation seem most clear. Even if an application
is trying to prevent leaking metadata, it could benefit from signals
from network about sudden capacity changes that can help it adapt its
application quality, such as bitrates and codecs. Such signalling
may not be appropriate for the most privacy-sensitive applications,
like Tor, but could be applicable for many others. There are
existing protocols that involve explicit signaling between
applications and networks, such as ECN [RFC3168], but that has yet to
see wide adoption.
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Managed networks (such a private corporate networks) was brought up
in several comments as a particularly challenging area for being able
to meet management requirements while maintaining encryption and
privacy. These networks can have legal and regulated requirements
for detection of specific fraudulent or malicious traffic.
Personal networks that enable managed parental controls have similar
complications with encrypted traffic and user privacy. In these
scenarios, the parental controls being operated by the network may be
as simple as a DNS filter, an can be made ineffective by a device
routing traffic to an alternate DNS resolver.
2.2. "Where we want to go" - Collaboration Principles
The second day of the workshop agenda focused on the emerging
techniques for analysing, managing or monitoring encrypted traffic.
Presentations ranged from discussing advanced classification and
identification, including machine-learning techniques, for the
purposes of manging network flows, monitoring or monetising usage.
After an introduction that covered the goals of the workshop and the
starting questions (as described in Section 1), there were three
presentations, followed by open discussion.
2.2.1. First party collaboration for network management
It is the intention of encryption to create a barrier between
entities inside the communication and everyone else, including
network operators when we are talking about end-to-end encryption of
traffic. Any attempt, therefore, to overcome that intentional
barrier requires an intent to collaborate between the inside and
outside entities. Those entities must, at a minimum, agree on the
benefits to overcoming the barrier (or solving the problem), that
costs are proportional to the beenfits, and to additional
limitations, or safeguards, against bad behaviour by collaborators
including the inclusion of other non-insiders [BARNES].
The internet is designed interoperably, which means an outside entity
wishing to collaborate with the inside might be any number of
intermediaries and not, say, a specific person that can be trusted in
the human sense. Additionally the use of encryption, especially
network or transport encryption, introduces dynamic or
opportunitistic or perfunctory discoverability. These realities both
point to a need to interrogate the reason why any outside entity
might make an engineering case to collaborate with the user of an
encrypted network, and whether the tradeoffs and potential risks are
worth it to the user.
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However the answers cannot be specific and the determinations or
guidance need to be general as the encryption boundary is inevitably
an application used by many people. Tradeoffs must make sense to
users who are unlikely to be thinking about network management
considerations. Harms need to be preemptively reduced because in
general terms few users would choose network management benefits over
their own privacy if given the choice.
Additionally there appear to be little if any actual evidence that
encryption is causing user-meaningful network problems. Since
alignment on problem solving is a prerequisite to collaboration on a
solution it does not seem that collaboration across the encryption
boundary is called for.
2.2.2. Second and third party collaboration for network management
Even with the wide-scale deployment of encryption in new protocols
and techniques that prevent passive observers of network traffic from
knowing the content of exchanged communications, important
information such as which parties communicate and sometimes even
which services have been requested may still be able to be deduced.
The future is to conceal more data and metadata from passive
observers and also to minimize information exposure to second parties
(were the user is the first party) by, maybe counterintuitively,
introducing third-party relay services to intermediate
communications. As discussed in [KUEHLEWIND], the relay is a
mechanism to separate, using additional levels of encryption, two
important pieces of information: knowledge of the identity of the
person accessing a service is separated from knowledge about the
service being accessed. By contrast a VPN uses only one level of
encryption and does not separate identity (first party) and service
(second party) metadata.
Relay mechanisms are termed "oblivious", there is a future for
specifications in privacy-preserving measurement (PPM), and protocols
like Multiplexed Application Substrate over QUIC Encryption (MASQUE)
are discussed in the IETF. In various schemes users are ideally able
to share their identity only with the entity they have identified as
a trusted one. That data is not shared with the service provider.
However this is more complicated for network management, but there
may be opportunities for better collaboration between the network
and, say, the application or service at the endpoint.
A queriable relay mechanism could preserve network management
functions that are disrupted by encryption, such as TCP optimisation,
quality of service, zero-rating, parental controls, access control,
redirection, content enhancement, analytics and fraud prevention.
Instead of encrypted communication between only two between the ends
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and passive observation by all on-path elements, intermediate relays
could be trusted parties with limited information for the purposes of
collaboration between in-network intermediary services' support.
2.2.3. Visible, optional network management
In encrypted communications, out of all of the possible network
management functions that might be ameliorated by proxying the
ability to control congestion has been researched in depth. These
techniques are realized based on TCP performance enhancing proxies
(PEP) that either entirely intercept a TCP connection or interfere
with the transport information in the TCP header. However, beside
the challenge that new encrypted protocol limited any such in-network
interference, these techniques can also have negative impact on the
evolvability of these protocols. Therefore, instead on manipulating
existing information, a new approaches was presented where additional
information is send using a so-called side-car protocol independent
of the main transport protocol that is used end-to-end [WELZL]. E.g.
side car information can contain additional acknowledgements to
enable in-network local retransmission faster end-to-end
retransmission by reducing the signaling round trip time.
Taking user privacy benefits for granted, there is a need to
investigate the comparable performance outputs of various encrypted
traffic configurations such as use of an additional "side-car"
protocol, or explicit encrypted and trusted network communication
using MASQUE in relation to existing techniques based TCP performance
enhancing proxies (PEP), etc.
2.2.4. Discussion
One size fits all? On the issue of trust, different networks or
devices are going to have different requirements for the level of
trust that they have in devices, users or each other, and vice versa.
For example, imagine networks with really different security
requirements, like protecting children in a home versus a national
security institution. How could one network architecture solve the
needs of all use cases?
Does our destination have consequences? It seems sometimes that
there may be consequences many years down the line of ubiquitous,
strong encryption of network traffic because it will cause a reaction
by intermediaries to find ways to poke holes in what are supposed to
be long-term solutions for user privacy and security.
Can we bring the user along? While there has been a focus on the
good reasons for why people might collaborate across the encryption
barrier, there will always be others who want to disrupt that because
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they are motivated to exploit the data for their own gain, and
sometimes this is called innovation. What high-level policy
mitigations hvae done is to expose how powerless end users are to
corporate practices of data harvesting. And yet interfaces to help
users understand these lower layer traffic flows to protect their
financial transactions or privacy haven't been achieved yet. That
means that engineers are having to make inferences about what users
want. Instead we should be making these relationships and tradeoffs
more visible.
2.3. "How we get there" - Collaboration Use cases
The third day focused on techniques that could actually be used to
improve management of encrypted networks. A central theme of all of
the presentations about potential proposed paths forward included
some element of collaboration between networks and subscribing
clients that simultaneously want both privacy and protection. Thus,
the central theme in the third day became negotiation and
collaboration.
2.3.1. Establishing expected contracts to enable security management
When thinking about enterprise networks where client behavior is
potentially managed, [COLLINS] proposes "Improving network monitoring
through contracts", where contracts describe different states of
network behavior.
Because network operators have a limited amount of time to focus on
problems and process alerts, contracts and states let the operator
focus on a particular aspect of a current situation or problem. The
current estimate for the number of events an SOC operator can handle
is about 10 per hour. Operators must work within the limits imposed
by their organization, and must pick between options that frequently
only frustrate attackers -- entirely preventing attacks is
potentially impossible. Finally, operators must prioritize and
manage the most events possible.
Validating which alerts are true positives is challenging because
lots of weird traffic creates many anomalies and not all anomalies
are malicious events. Identifying what anomalous traffic is rooted
in malicious activity with any level of certainty is extremely
challenging. Unfortunately, applying the latest machine learning
techniques has only produced mixed results. To make matters worse,
the large amounts of Internet-wide scanning has resulted in endless
traffic that is technically malicious but only creates an information
overload and challenges event prioritization. Any path forward must
succeed in freeing up analyst time to concentrate on the more
challenging events.
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The proposed contract solution is to define a collection of
acceptable behaviors categorized into a envelope of different states
that might include IP addresses, domain names, and indicators of
compromise. Deviation from a contract might indicate that a system
is acting outside a normal mode of behavior, or even that a normal
mode of behavior is suddenly missing. An example contracts might be
"this system is expected to update its base OS once a day", and if
this doesn't occur then this expectation has not been met and the
system should be checked as it failed to call home to look for
(potentially security related) updates.
Within the IETF, the Manufacturer Usage Description Specification
(MUDD) {?RFC8520} specification is one subset of contracts. Note
that contracts are likely to only succeed in a constrained, expected
environment maintained by operational staff, and may not work in an
open internet environment where end users are driving all network
connections.
2.3.2. Zero Knowledge Middleboxes
The world is not only shifting to increased encrypted traffic, but is
also encrypting more and more of the metadata (e.g. DNS queries and
responses). This makes network policy enforcement by middleboxes
significantly more challenging. The result is the creation of a
significant tension between security enforcement and privacy
protection.
A goal for solving this problem should include not weakening
encryption, should enable networks to enforce their policies, and
should ideally not require newly deployed server software. Existing
solutions fail with at least one of these points.
A cryptographic principle of a "zero knowledge proof" (ZKP) [GRUBBS]
may be one path forward to consider. A ZKP allows a third party to
verify that a statement is true, without revealing what the statement
actually is. Applying this to network traffic has been shown to
allow a middlebox to verify that traffic to a web server is actually
compliant with a policy without revealing the actual contents. This
solution meets the above three criteria. Using ZKP within TLS 1.3
traffic turns out to be plausible.
An example engine was built to test ZKP using encrypted DNS. Clients
were able to create DNS requests that were not listed within a DNS
block list. Middleboxes could verify, without knowing the exact
request, that the client's DNS request was not in the prohibited
list. Although the result was functional, the computational overhead
was still too slow and future work will be needed to decrease the ZKP
imposed latencies.
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2.3.3. Red Rover - A collaborative approach to content filtering
The principle challenge being studied is how to deal with the inherit
conflict between filtering and privacy. Network operators need to
implement policies and regulations that can originate from many
locations (e.g. security, governmental, parental, etc). Conversely,
clients need to protect user's privacy and user security.
Safe browsing, originally created by Google, is one example of a
mechanism that tries to meet both sides of this conflict. It would
be beneficial to standardize this and other similar mechanisms.
Operating systems could continually protect their users by ensuring
that malicious destinations are not being reached. This would
require some coordination between cooperating clients and servers
offering protection services. These collaborative solutions may be
the best compromise between the tension of privacy vs protection
based services [PAULY].
3. Conclusions
Looking forward, the workshop participants identified that solving
the entire problem space with a single approach will be challenging
for a number of reasons. First, scalability of many solutions will
likely be an issue as some solutions are expensive in implementation.
Collaboration between multiple parties will be required for many
mechanisms to function. Finally, there is an unanswered question of
whether or not network operators be willing to participate and allow
technologies into their environment requirements in exchange for
technologies that prove their clients are being good net-citizens.
If so, some of these solutions might be required to exist before
networks allow certain type of increased encryption; consider the
example of TLS Encrypted Client Hello being blocked by some network
operators.
The breadth of the problem space itself is another complicating
factor. A wide variety of networks architectures exist that have
different requirements for both data encryption and network
management. Each problem space will have different encumbrances of
multiple types; for example, technical, legal, data ownership, adn
regulatory concerns. New network architectures might be needed to
solve this problem at a larger scope, which would in turn require
interoperability support from network product vendors. In the end,
we should recognize that one solution will not solve all these cases
and it is more likely that different use cases will require different
solutions. Education about various solutions will be required in
order to ensure regulation and policy organizations can understand
and thus support the deployment of developed solutions.
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4. Informative References
[BARNES] Barnes, R., "What’s In It For Me? Revisiting the reasons
people collaborate", August 2022,
<https://github.com/intarchboard/m-ten-
workshop/blob/main/papers/Barnes-Whats-In-It-For-Me-
Revisiting-the-reasons-people-collaborate.pdf>.
[CASAS] Casas, P., "Monitoring User-Perceived Quality in an
Encrypted Internet", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Casas-AI-driven-real-time-QoE-
monitoring-encrypted-traffic.pdf>.
[COLLINS] Collins, M., "Improving Network Monitoring Through
Contracts", August 2022, <https://github.com/intarchboard/
workshop-m-ten/blob/main/papers/Collins-Improving-Network-
Monitoring-Through-Contracts.pdf>.
[DERI] Deri, L., "nDPI Research Proposal", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Deri-nDPI-Research-Proposal.pdf>.
[DITTO] Meier, R., Lenders, V., and L. Vanbever, "Ditto - WAN
Traffic Obfuscation at Line Rate", April 2022,
<https://nsg.ee.ethz.ch/fileadmin/user_upload/
publications/ditto_final_ndss22.pdf>.
[ELKINS] Elkins, N., Ackermann, M., Tahiliani, M., Dhody, D., and
T. Pecorella, "Performance Monitoring in Encrypted
Networks", August 2022, <https://github.com/intarchboard/
workshop-m-ten/blob/main/papers/Elkins-Performance-
Monitoring-in-Encrypted-Networks-PDMv2.pdf>.
[GRUBBS] Grubbs, P., Arun, A., Zhang, Y., Bonneau, J., and M.
Walfish, "Zero-Knowledge Middleboxes", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Grubbs-Zero-
Knowledge%20Middleboxes.pdf>.
[I-D.irtf-pearg-safe-internet-measurement]
Learmonth, I. R., Grover, G., and M. Knodel, "Guidelines
for Performing Safe Measurement on the Internet", Work in
Progress, Internet-Draft, draft-irtf-pearg-safe-internet-
measurement-06, 19 August 2022,
<https://datatracker.ietf.org/doc/html/draft-irtf-pearg-
safe-internet-measurement-06>.
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[JIANG] Jiang, X., Liu, S., Naama, S., Bronzino, F., Schmitt, P.,
and N. Feamster, "Towards Designing Robust and Efficient
Classifiers for Encrypted Traffic in the Modern Internet",
August 2022, <https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Jiang-Towards-Designing-Robust-and-
Efficient-Classifiers-for-Encrypted-Traffic-in-the-Modern-
Internet.pdf>.
[KNODEL] Knodel, M., "Guidelines for Performing Safe Measurement on
the Internet", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Knodel-Guidelines-for-Performing-
Safe-Measurement-on-the-Internet.pdf>.
[KUEHLEWIND]
Kühlewind, M., Westerlund, M., Sarker, Z., and M. Ihlar,
"Relying on Relays", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Kuehlewind-Relying-on-Relays.pdf>.
[LEI] Lei, Y., Wu, J., Sun, X., Zhang, L., and Q. Wu, "Encrypted
Traffic Classification Through Deep Learning", August
2022, <https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Lei-Encrypted-Traffic-Classification-
Through-Deep-Learning.pdf>.
[PAULY] Pauly, T. and R. Barnes, "Red Rover", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Pauly-Red-Rover-A-collaborative-
approach-to-content-filtering.pdf>.
[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP",
RFC 3168, DOI 10.17487/RFC3168, September 2001,
<https://www.rfc-editor.org/rfc/rfc3168>.
[WELZL] Welzl, M., "The Sidecar", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Welzl-The-Sidecar-Opting-in-to-PEP-
Functions.pdf>.
[WU] Wu, Q., Wu, J., and Q. Ma, "Network Management of
Encrypted Traffic", August 2022,
<https://github.com/intarchboard/workshop-m-
ten/blob/main/papers/Wu-mten-taxonomy.pdf>.
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Appendix A. Position Papers
Interested participants were openly invited to submit position papers
on the workshop topics, including Internet-Drafts, relevant academic
papers, or short abstracts explaining their interest. The papers
below constitute the inputs that were considered relevant for
workshop attendees and that focused the discussions themselves. The
program committee grouped the papers by theme as such.
A.1. Motivations and principles
Richard Barnes. “What’s In It For Me? Revisiting the reasons people
collaborate.” [BARNES]
Iain R. Learmonth, Gurshabad Grover, Mallory Knodel. “Guidelines for
Performing Safe Measurement on the Internet.” (Additional rationale)
[KNODEL]
Qin Wu, Jun Wu, Qiufang Ma. “Network Management of Encrypted Traffic:
Detect it don’t decrypt it.” [WU]
A.2. Classification and identification of encrypted traffic
Luca Deri. “nDPI Research Proposal.” [DERI]
Wes Hardaker. “Network Flow Management by Probability.”
Xi Jiang, Shinan Liu, Saloua Naama, Francesco Bronzino, Paul Schmitt,
Nick Feamster. “Towards Designing Robust and Efficient Classifiers
for Encrypted Traffic in the Modern Internet.” [JIANG]
Yupeng Lei, Jun Wu, Xudong Sun, Liang Zhang, Qin Wu. “Encrypted
Traffic Classification Through Deep Learning.” [LEI]
A.3. Ideas for collaboration and coordination between devices and
networks
Michael Collins. “Improving Network Monitoring Through Contracts.”
[COLLINS]
Paul Grubbs, Arasu Arun, Ye Zhang, Joseph Bonneau, Michael Walfish.
“Zero-Knowledge Middleboxes.” [GRUBBS]
Mirja Kühlewind, Magnus Westerlund, Zaheduzzaman Sarker, Marcus
Ihlar. “Relying on Relays: The future of secure communication.”
[KUEHLEWIND]
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Tommy Pauly, Richard Barnes. “Red Rover: A collaborative approach to
content filtering.” [PAULY]
Michael Welzl. “The Sidecar: ‘Opting in’ to PEP Functions.“ [WELZL]
A.4. Other background material
Pedro Casas. “Monitoring User-Perceived Quality in an Encrypted
Internet – AI to the Rescue.” [CASAS]
Nalini Elkins, Mike Ackermann, Mohit P. Tahiliani, Dhruv Dhody,
Prof. Tommaso Pecorella. “Performance Monitoring in Encrypted
Networks: PDMv2.” [ELKINS]
Appendix B. Workshop participants
The workshop participants were Cindy Morgan, Colin Perkins, Cullen
Jennings, Deborah Brungard, Dhruv Dhody, Eric Vyncke, Georg Carle,
Ivan Nardi, Jari Arkko, Jason Livingood, Jiankang Yao, Karen
O'Donoghue, Keith Winstein, Lars Eggert, Laurent Vanbever, Luca Deri,
Mallory Knodel, Marcus Ihlar, Matteo, Michael Ackermann, Michael
Collins, Michael Richardson, Michael Welzl, Mike Ackermann, Mirja
Kühlewind, Mohit P. Tahiliani, Nalini Elkins, Patrick Tarpey, paul
grubbs, Pedro Casas, Qin Wu, Qiufang, Richard Barnes, Rob Wilton,
Russ White, Saloua Naama, Shinan Liu, Srinivas C, Toerless Eckert,
Tommy Pauly, Wes Hardaker, Xi Chase Jiang, Zaheduzzaman Sarker,
Zhenbin Li.
Appendix C. Program Committee
The workshop program committee members were Wes Hardaker (IAB, USC/
ISI), Mallory Knodel (IAB, Center for Democracy and Technology),
Mirja Kühlewind (IAB, Ericsson), Tommy Pauly (IAB, Apple), Russ White
(IAB, Juniper), Qin Wu (IAB, Huawei).
Acknowledgments
TODO acknowledge.
Authors' Addresses
Mallory Knodel
Center for Democracy & Technology
Email: mknodel@cdt.org
Wes Hardaker
Email: ietf@hardakers.net
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Tommy Pauly
Email: tpauly@apple.com
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