Internet Architecture Board (IAB) M. Knodel
Request for Comments: 9490
Category: Informational W. Hardaker
ISSN: 2070-1721
T. Pauly
January 2024
Report from the IAB Workshop on Management Techniques in Encrypted
Networks (M-TEN)
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 expressed during the workshop by participants and do not
necessarily reflect IAB views and positions.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Architecture Board (IAB)
and represents information that the IAB has deemed valuable to
provide for permanent record. It represents the consensus of the
Internet Architecture Board (IAB). Documents approved for
publication by the IAB are not candidates for any level of Internet
Standard; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc9490.
Copyright Notice
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Table of Contents
1. Introduction
1.1. About This Workshop Report Content
2. Workshop Scope and Discussion
2.1. "Where We Are" - Requirements and Passive Observations
2.1.1. Traffic Classification and Network Management
2.1.2. Preventing Traffic Analysis
2.1.3. Users and Privacy
2.1.4. Discussion
2.2. "Where We Want to Go" - Collaboration Principles
2.2.1. First-Party Collaboration for Network Management
2.2.2. Second- and Third-Party Collaboration for Network
Management
2.2.3. Visible, Optional Network Management
2.2.4. Discussion
2.3. "How We Get There" - Collaboration Use Cases
2.3.1. Establishing Expected Contracts to Enable Security
Management
2.3.2. Zero-Knowledge Middleboxes
2.3.3. Red Rover - a Collaborative Approach to Content
Filtering
3. Conclusions
4. Informative References
Appendix A. Position Papers
A.1. Motivations and Principles
A.2. Classification and Identification of Encrypted Traffic
A.3. Ideas for Collaboration and Coordination between Devices
and Networks
A.4. Other Background Material
Appendix B. Workshop Participants
Appendix C. Program Committee
IAB Members at the Time of Approval
Acknowledgments
Authors' Addresses
1. Introduction
The Internet Architecture Board (IAB) holds occasional workshops
designed to consider long-term issues and strategies for the
Internet, and to suggest future directions for the Internet
architecture. This long-term planning function of the IAB is
complementary to the ongoing engineering efforts performed by working
groups of the Internet Engineering Task Force (IETF).
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 to
support 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 to initiate 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?
1.1. About This Workshop Report Content
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.
Furthermore, the content of the report comes from presentations given
by workshop participants and notes taken during the discussions,
without interpretation or validation. Thus, the content of this
report follows the flow and dialog of the workshop but does not
attempt to capture a consensus.
2. Workshop Scope and Discussion
The workshop was held across three days with 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 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 techniques are passive in nature:
they don't rely on 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 commonly 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 useful insight into how "leaky" the protocols used by
applications are and points to areas where information is visible to
any observer, who may or may not be malicious.
Frequently, classification has been based on specific rules crafted
by experts, but there is also a move toward using machine 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 show that a model that performed with high accuracy on an
initial data set becomes severely degraded when running on a newer
data set that contains 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 to determine which set of features in IP packets are
most useful for focused machine-learning analysis. [WU] also
recommends further research investment in Artificial Intelligence
(AI) analysis for network management.
2.1.2. Preventing Traffic Analysis
Just as traffic classification is continually adapting, techniques to
prevent traffic analysis and to 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 by adding padding to 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 inline speed.
While traffic obfuscation techniques are not widely deployed today,
this study underlines the need for continuous effort to keep traffic
models updated over time, the challenges of the classification of
encrypted traffic, as well as the opportunities to further enhance
user privacy.
2.1.3. Users and Privacy
The Privacy Enhancements and Assessments Research Group (PEARG) is
working on a document to discuss guidelines for measuring traffic on
the Internet in a safe and privacy-friendly way [LEARMONTH]. These
guidelines and principles provide another view on 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 given explicitly as informed consent, given by proxy,
or may 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 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 in others. One of the
recurring challenges that was discussed was the lack of a clear way
to understand or to 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 an attempt by the network to inspect application
traffic without coordination from applications, and traffic
obfuscation is an attempt by the application 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 the leaking of metadata, it could benefit from
signals from the network about sudden capacity changes that can help
it adapt its application quality, such as bitrates and codecs. Such
signaling 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 Explicit Congestion Notification
(ECN) [RFC3168], but that has yet to see wide adoption.
Managed networks (such as private corporate networks) were brought up
in several comments as particularly challenging for meeting
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 that are operated by the network may
be as simple as a DNS filter, which 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 focused on the emerging techniques for
analyzing, managing, or monitoring encrypted traffic. Presentations
covered advanced classification and identification, including
machine-learning techniques, for the purposes of managing network
flows or monitoring or monetizing 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 intent of end-to-end encryption of traffic to create a
barrier between entities inside the communication channel and
everyone else, including network operators. Therefore, any attempt
to overcome that intentional barrier requires collaboration between
the inside and outside entities. At a minimum, those entities must
agree on the benefits of overcoming the barrier (or solving the
problem), agree that costs are proportional to the benefits, and
agree to additional limitations or safeguards against bad behavior by
collaborators including 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-layer or transport-layer encryption, introduces dynamic or
opportunistic or perfunctory discoverability. These realities point
to a need to ask why an outside entity might make an engineering case
to collaborate with the user of a network with encrypted traffic and
to ask whether the trade-offs and potential risks are worth it to the
user.
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. Trade-offs 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.
Some have found that there appears to be little, if any, evidence
that encryption causes network problems that are meaningful to the
user. 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 of 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
(where 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 that uses additional levels of encryption to separate 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 optimization,
quality of service, zero-rating, parental controls, access control,
redirection, content enhancement, analytics, and fraud prevention.
Instead of encrypting communication between only two ends with
passive observation by all on-path elements, intermediate relays
could be introduced as trusted parties that get to see limited
information for the purpose of collaboration between in-network
intermediary services.
2.2.3. Visible, Optional Network Management
Out of all of the possible network management functions that might be
ameliorated by proxying, the ability to control congestion in
encrypted communications has been researched in depth. These
techniques are realized based on TCP performance-enhancing proxies
(PEPs) that either entirely intercept a TCP connection or interfere
with the transport information in the TCP header. However, despite
the challenge that the new encrypted protocol will limit any such in-
network interference, these techniques can also have a negative
impact on the evolvability of these protocols. Therefore, a new
approach was presented where, instead of manipulating existing
information, additional information is sent using a so-called sidecar
protocol independent of the main transport protocol that is used end
to end [WELZL]. For example, sidecar information can contain
additional acknowledgments to enable in-network local retransmission
or 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 the use of an additional sidecar
protocol, or explicit encrypted and trusted network communication
using MASQUE in relation to existing techniques such as TCP PEPs,
etc.
2.2.4. Discussion
One size fits all? On the issue of trust, different networks or
devices will have different trust requirements for devices, users, or
each other, and vice versa. For example, imagine two networks with
really different security requirements, like a home network with a
requirement to protect its child users versus a national security
institution's network. How could one network architecture solve the
needs of all use cases?
Does our destination have consequences? It seems sometimes that
there may be future consequences caused by the ubiquitous, strong
encryption of network traffic because it will cause intermediaries 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 why people might collaborate across the encryption
barrier, there will always be others who want to disrupt that in
order to exploit the data for their own gain, and sometimes
exploitation is called innovation. High-level policy mitigations
have exposed how powerless end users are against 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 must make inferences about user wants. Instead, we should
make these relationships and trade-offs more visible.
2.3. "How We Get There" - Collaboration Use Cases
The third day focused on techniques that could be used to improve the
management of encrypted networks.
The potential paths forward described in the presentations included
some element of collaboration between the networks and the
subscribing clients that simultaneously want both privacy and
protection. Thus, the central theme of the third day became
negotiation and collaboration.
2.3.1. Establishing Expected Contracts to Enable Security Management
For 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 a Security Operations
Center (SOC) operator can handle is about 10 per hour. Operators
must work within the limits imposed by their organization and must
pick among options that frequently only frustrate attackers --
preventing attacks entirely 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 which anomalous traffic is rooted
in malicious activity with any level of certainty is extremely
challenging. Unfortunately, applying the latest machine-learning
techniques has 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
free up analyst time to concentrate on the more challenging events.
The proposed contract solution is to define a collection of
acceptable behaviors that comprises 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 contract might be "this
system is expected to update its base OS once a day". 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
(MUD) [RFC8520] is one subset of contracts. Note that contracts are
likely to succeed only in a constrained, expected environment
maintained by operational staff and may not work in an open Internet
environment where end users drive 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 a significant tension
between security enforcement and privacy protection.
Goals for solving this problem should include enabling networks to
enforce their policies, but should not include the weakening of
encryption nor the deployment of new server software. Existing
solutions fail to meet 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 compliant
with a policy without revealing the actual contents. This solution
meets the three criteria listed above. Using ZKP within TLS 1.3
traffic turns out to be plausible.
An example engine using encrypted DNS was built to test ZKP. 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 on 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.
2.3.3. Red Rover - a Collaborative Approach to Content Filtering
The principle challenge being studied is how to handle the inherent
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 their users' privacy and
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 to resolve the tension between privacy services
and protection services [PAULY].
3. Conclusions
Looking forward, the workshop participants identified that solving
the entire problem space with a single approach will be challenging
for several reasons:
* The scalability of many solutions will likely be an issue as some
solutions are complex or expensive to implement.
* Collaboration between multiple parties will be required for many
mechanisms to function, and the sets of parties required for
different use cases might be disjoint.
* There is an unanswered question of whether or not network
operators are willing to participate by allowing new encryption
technologies into their environment 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 a 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. There is a wide variety of network architectures, and each
has different requirements for both data encryption and network
management. Each problem space will have multiple, different
encumbrances: for example, technical, legal, data ownership, and
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. 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.
After new technologies and related standards are developed and
deployed, unintended consequences can emerge. These lead to effects
in multiple directions: on one hand, exposed protocol values not
intended for network management might be used by networks to
differentiate traffic; on the other hand, changes to a protocol that
break existing use cases might have an impact on private network
deployments. While making decisions on technology direction and
protocol design, it is important to consider the impact on various
kinds of network deployments and their unique requirements. When
protocols change to make different network management functions
easier or harder, the impact on various deployment models ought to be
considered and documented.
4. Informative References
[BARNES] Barnes, R., "What's In It For Me? Revisiting the reasons
people collaborate", August 2022, <https://www.iab.org/wp-
content/IAB-uploads/2023/11/Barnes-Whats-In-It-For-Me-
Revisiting-the-reasons-people-collaborate.pdf>.
[CASAS] Casas, P., "Monitoring User-Perceived Quality in an
Encrypted Internet - AI to the Rescue", August 2022,
<https://www.iab.org/wp-content/IAB-uploads/2023/11/Casas-
AI-driven-real-time-QoE-monitoring-encrypted-traffic.pdf>.
[COLLINS] Collins, M., "Improving Network Monitoring Through
Contracts", August 2022, <https://www.iab.org/wp-content/
IAB-uploads/2023/11/Collins-Improving-Network-Monitoring-
Through-Contracts.pdf>.
[DERI] Deri, L., "nDPI Research Proposal", August 2022,
<https://www.iab.org/wp-content/IAB-uploads/2023/11/Deri-
nDPI-Research-Proposal.pdf>.
[DITTO] Meier, R., Lenders, V., and L. Vanbever, "ditto: WAN
Traffic Obfuscation at Line Rate", Network and Distributed
Systems Security (NDSS) Symposium,
DOI 10.14722/ndss.2022.24056, April 2022,
<https://doi.org/10.14722/ndss.2022.24056>.
[ELKINS] Elkins, N., Ackermann, M., Tahiliani, M., Dhody, D., and
T. Pecorella, "Performance Monitoring in Encrypted
Networks: PDMv2", August 2022, <https://www.iab.org/wp-
content/IAB-uploads/2023/11/Elkins-Performance-Monitoring-
in-Encrypted-Networks-PDMv2.pdf>.
[GRUBBS] Grubbs, P., Arun, A., Zhang, Y., Bonneau, J., and M.
Walfish, "Zero-Knowledge Middleboxes", 31st USENIX
Security Symposium (USENIX Security 22), August 2022,
<https://www.usenix.org/conference/usenixsecurity22/
presentation/grubbs>.
[HARDAKER] Hardaker, W., "Network Flow Management by Probability",
August 2022, <https://www.iab.org/wp-content/IAB-
uploads/2023/11/Hardaker-Encrypted-Traffic-
Estimation.pdf>.
[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://www.iab.org/wp-content/IAB-
uploads/2023/11/Jiang-Towards-Designing-Robust-and-
Efficient-Classifiers-for-Encrypted-Traffic-in-the-Modern-
Internet.pdf>.
[KNODEL] Knodel, M., "(Introduction) 'Guidelines for Performing
Safe Measurement on the Internet'", August 2022,
<https://www.iab.org/wp-content/IAB-uploads/2023/11/
Knodel-Guidelines-for-Performing-Safe-Measurement-on-the-
Internet.pdf>.
[KUEHLEWIND]
Kuehlewind, M., Westerlund, M., Sarker, Z., and M. Ihlar,
"Relying on Relays: The future of secure communication",
June 2022, <https://www.ericsson.com/en/blog/2022/6/
relays-and-online-user-privacy>.
[LEARMONTH]
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-09, 12 January 2024,
<https://datatracker.ietf.org/doc/html/draft-irtf-pearg-
safe-internet-measurement-09>.
[LEI] Lei, Y., Wu, J., Sun, X., Zhang, L., and Q. Wu, "Encrypted
Traffic Classification Through Deep Learning", August
2022, <https://www.iab.org/wp-content/IAB-uploads/2023/11/
Lei-Encrypted-Traffic-Classification-Through-Deep-
Learning.pdf>.
[PAULY] Pauly, T. and R. Barnes, "Red Rover: A collaborative
approach to content filtering", August 2022,
<https://www.iab.org/wp-content/IAB-uploads/2023/11/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/info/rfc3168>.
[RFC8520] Lear, E., Droms, R., and D. Romascanu, "Manufacturer Usage
Description Specification", RFC 8520,
DOI 10.17487/RFC8520, March 2019,
<https://www.rfc-editor.org/info/rfc8520>.
[WELZL] Welzl, M., "The Sidecar: 'Opting in' to PEP Functions",
August 2022, <https://www.iab.org/wp-content/IAB-
uploads/2023/11/Welzl-The-Sidecar-Opting-in-to-PEP-
Functions.pdf>.
[WU] Wu, Q., Wu, J., and Q. Ma, "Network Management of
Encrypted Traffic: Detect it don't decrypt it", August
2022, <https://www.iab.org/wp-content/IAB-uploads/2023/11/
Wu-mten-taxonomy.pdf>.
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.
A.1. Motivations and Principles
Richard Barnes. "What's In It For Me? Revisiting the reasons people
collaborate." [BARNES]
Mallory Knodel. "(Introduction) '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." [HARDAKER]
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 Kuehlewind, Magnus Westerlund, Zaheduzzaman Sarker, Marcus
Ihlar. "Relying on Relays: The future of secure communication."
[KUEHLEWIND]
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, Éric 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 Collins, Michael
Richardson, Michael Welzl, Mike Ackermann, Mirja Kühlewind, Mohit
P. Tahiliani, Nalini Elkins, Patrick Tarpey, Paul Grubbs, Pedro
Casas, Qin Wu, Qiufang Ma, Richard Barnes, Rob Wilton, Russ White,
Saloua Naama, Shinan Liu, Srinivas C, Toerless Eckert, Tommy Pauly,
Wes Hardaker, Xi Chase Jiang, Zaheduzzaman Sarker, and 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).
IAB Members at the Time of Approval
Internet Architecture Board members at the time this document was
approved for publication were:
Dhruv Dhody
Lars Eggert
Wes Hardaker
Cullen Jennings
Mallory Knodel
Suresh Krishnan
Mirja Kühlewind
Tommy Pauly
Alvaro Retana
David Schinazi
Christopher Wood
Qin Wu
Jiankang Yao
Acknowledgments
We wish to acknowledge the comments and suggestions from Elliot Lear
and Arnaud Taddei for their comments and improvements to this
document.
Authors' Addresses
Mallory Knodel
Email: mknodel@cdt.org
Wes Hardaker
Email: ietf@hardakers.net
Tommy Pauly
Email: tpauly@apple.com
