



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

   Copyright (c) 2024 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.

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
