Independent Submission                                       M. Blanchet
Request for Comments: 9564                                      Viagenie
Category: Informational                                     1 April 2024
ISSN: 2070-1721


               Faster Than Light Speed Protocol (FLIP)

Abstract

  The recent advances in artificial intelligence (AI) such as large
  language models enable the design of the Faster than LIght speed
  Protocol (FLIP) for Internet.  FLIP provides a way to avoid
  congestion, enhance security, and deliver faster packets on the
  Internet by using AI to predict future packets at the receiving peer
  before they arrive.  This document describes the protocol, its
  various encapsulations, and some operational considerations.

Status of This Memo

  This document is not an Internet Standards Track specification; it is
  published for informational purposes.

  This is a contribution to the RFC Series, independently of any other
  RFC stream.  The RFC Editor has chosen to publish this document at
  its discretion and makes no statement about its value for
  implementation or deployment.  Documents approved for publication by
  the RFC Editor 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/rfc9564.

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
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  to this document.

Table of Contents

  1.  Introduction
  2.  Protocol Peer Preparation
  3.  FLIP Header
  4.  Protocol Operation
  5.  Versioning
  6.  Future Work
  7.  IANA Considerations
  8.  Security Considerations
  9.  Informative References
  Acknowledgements
  Author's Address

1.  Introduction

  ChatGPT was introduced to the public on 30 November 2022 [CHATGPT].
  Since then, large language models (LLMs) have been used for a large
  variety of applications.  It demonstrates the powerful ability to
  generate precise output based on the input and based on the
  appropriate training of the LLM.  This protocol specification uses
  this ability to predict future packets before they arrive at the
  receiving peer, therefore achieving faster-than-light-speed delivery,
  hence the protocol name: Faster than LIght speed Protocol (FLIP).

  Since FLIP can predict packets, frames, strings, or byte streams, it
  could be used at any layer of the IP protocol stack.  Moreover, with
  proper training, FLIP can also predict future encrypted packets, as
  encryption is just strings of bytes.  This specification shows FLIP
  as a Layer 2 shim as well as a transport shim layer.  Since FLIP can
  be used at any layer, it is expected that additional specifications
  will be created, such as predicting HTTP requests and answers, email
  content, and more.

  Since communications in deep space are unfortunately limited to light
  speed, and given the very large distances between spacecrafts and
  Earth, the consequence is very long delays.  By offering faster-than-
  light-speed delivery, FLIP is a key enabler and addition to deep-
  space IP networking [IP-DEEP-SPACE].

2.  Protocol Peer Preparation

  In order to successfully achieve faster than light speed, the peers
  of any protocol layer used by FLIP must prepare their side of the
  connection with the right model trained for the specific case.  This
  document does not dictate any specific LLM, as the implementations
  may choose the one that best works for their use case and train them
  accordingly.  As with any LLM, it is paramount to use a lot of
  training data, such as packet captures, in a variety of conditions to
  produce the best trained model.  To avoid security, privacy, and
  legal issues, the specifics of which LLM is used, how it was trained,
  and what is the data set used, shall not be published nor disclosed
  in the protocol.

  As an example, an implementation may elect to collect a significant
  number of Packet Capture (PCAP) files from tcpdump wiretapping at
  various vantage points on the Internet.  The fact that traffic may be
  encrypted is not an issue, since a well-trained LLM will be able to
  predict encrypted traffic as accurately as unencrypted traffic.

3.  FLIP Header

  Wherever FLIP is used (below IP, above IP or other transport, or at
  the application layer), a FLIP shim header is inserted.

     +----------+---------+----------------+----------------+
     |  Version | Command | Inner Protocol | Optional Data  |
     +----------+---------+----------------+----------------+

  The header contains the following fields:

  Version:  A field of variable and unspecified length that contains
     the SHA-256 hash of the model, used as the version, as described
     in Section 5.

  Command:  The codepoint identifying the operation of this FLIP frame.
     Commands are described in Section 4.  The initial list of valid
     FLIP commands is below.

     The maximum number size is infinite, given that artificial
     intelligence peers can support an infinite number of commands, by
     just updating their models without the need to update their
     protocol implementation.

                    +=========+===========+===========+
                    | Command | Codepoint | Reference |
                    +=========+===========+===========+
                    | model   | 0x01      | RFC 9564  |
                    +---------+-----------+-----------+
                    | data    | 0x02      | RFC 9564  |
                    +---------+-----------+-----------+

                                  Table 1

  Inner Protocol:  As the FLIP header is a shim header, the inner
     protocol is specified in this field.  For example, for a FLIP shim
     header inserted between IP and TCP, the IP packet will contain the
     FLIP codepoint as the transport protocol.  The FLIP inner protocol
     field will then contain the TCP codepoint that would otherwise be
     in the IP packet.

  Optional Data:  Some commands have additional data that are following
     the Command field.

  The header length is variable and depends on which command is used.
  Given the use of artificial intelligence by implementations of this
  protocol, the actual length of the header, and the length of each of
  its fields, is not specified in the header.  Instead, it is expected
  that the proper neural network on the receiver side will be able to
  find the actual header termination, thus saving many header bits.

  To properly signal the upper layer about the presence of the FLIP
  header, a specific codepoint is reserved at the layer below FLIP.
  Section 7 lists the registrations for IP and transport codepoints for
  this use.

4.  Protocol Operation

  Prior to sending a first packet using FLIP, the sender and the
  receiver should be configured with the appropriate model trained as
  discussed before.  It is left to the implementation to choose the
  right LLM and the right training data set.

  The following commands are defined:

  Model:  (codepoint 0x01).  This command provides a way for peers to
     send their model in-band of the FLIP protocol.  The model itself
     is carried in the Optional Data field of the FLIP header.  Prior
     to the actual model data, a MIME header is inserted with the
     proper media type.  If the media type for the model does not
     exist, it should be registered in the IANA Media Type registry.

  Data:  (codepoint 0x02).  This command tells the receiving peer that
     the data that follows can be predicted and therefore achieves
     faster-than-light-speed performance.

  Sending the model in-band to the other peer is an operation that
  should be done rarely, as models may be large in size.  Moreover, it
  actually discloses the model for any wiretapping adversary.
  Implementors may consider using a post-quantum cryptographic
  algorithm that is also immune to AI prediction, therefore a post-
  Quantum-AI cryptographic algorithm.

5.  Versioning

  As described in [RFC6709], most protocols should be designed to
  enable future enhancements, such as providing a way to signal a new
  version of the protocol.  In the case of FLIP, trained models will
  always be enhanced by new training.  A SHA-256 [RFC6234] hash of the
  trained model is used as a version number so each peer knows which
  FLIP version is being used.  The SHA-256 hash is put in version field
  in the FLIP header as described previously.  Given that new SHA-256
  hashes are not sequential but fully random, replay attacks of future
  predictions are prevented.

6.  Future Work

  This new protocol may revolutionize how we design Internet protocols
  and how we use the Internet.  For example, it is envisioned that this
  protocol may be used for video streaming, augmented reality, virtual
  reality, and post-quantum cryptography to name a few.  By predicting
  the future packets, all these protocols and applications can benefit
  the use of FLIP.

7.  IANA Considerations

  For FLIP, codepoints could be registered in the following IANA
  registries.

  *  Protocol Numbers [IANA-PN]: 345, FLIP, Faster than LIght speed
     Protocol, RFC 9564

  *  Service Name and Transport Protocol Port Number Registry
     [IANA-SN]: FLIP, 68534, udp and tcp, RFC 9564

8.  Security Considerations

  The ability to predict future packets based on LLMs can be used by
  adversaries that are listening to the traffic via wiretapping.  If
  they have access to the same model used by the destination peer, they
  could use it to predict the next packets and then initiate various
  attacks, including novel ones such as the "futureplay attack."
  Compared to the typical replay attack, this attack is where the
  adversary will predict future packets and then send them in advance
  to the destination.  While it may not be obvious at this time, these
  novel attacks should be investigated before they become a problem.
  Therefore, further research in this field is suggested.

  The ability for a peer to predict future packets enhances the overall
  security of the Internet because adversaries will not be able to
  inject bad packets in a connection, as the destination will be able
  to compare the received bad packet with the calculated prediction and
  therefore will easily identify and deny any bad packets.

9.  Informative References

  [CHATGPT]  Wikipedia, "ChatGPT", 20 March 2024,
             <https://en.wikipedia.org/w/
             index.php?title=ChatGPT&oldid=1214732037>.

  [IANA-PN]  IANA, "Protocol Numbers",
             <https://www.iana.org/assignments/protocol-numbers/>.

  [IANA-SN]  IANA, "Service Name and Transport Protocol Port Number
             Registry", <https://www.iana.org/assignments/service-
             names-port-numbers/>.

  [IP-DEEP-SPACE]
             Blanchet, M., Huitema, C., and D. Bogdanović, "Revisiting
             the Use of the IP Protocol Stack in Deep Space: Assessment
             and Possible Solutions", Work in Progress, Internet-Draft,
             draft-many-deepspace-ip-assessment-01, 4 March 2024,
             <https://datatracker.ietf.org/doc/html/draft-many-
             deepspace-ip-assessment-01>.

  [RFC6234]  Eastlake 3rd, D. and T. Hansen, "US Secure Hash Algorithms
             (SHA and SHA-based HMAC and HKDF)", RFC 6234,
             DOI 10.17487/RFC6234, May 2011,
             <https://www.rfc-editor.org/info/rfc6234>.

  [RFC6709]  Carpenter, B., Aboba, B., Ed., and S. Cheshire, "Design
             Considerations for Protocol Extensions", RFC 6709,
             DOI 10.17487/RFC6709, September 2012,
             <https://www.rfc-editor.org/info/rfc6709>.

Acknowledgements

  Since this protocol specification is using artificial intelligence
  and large language models, it was deemed that dumb humans must not
  review this specification.  Instead, the specification has been
  submitted to multiple LLM chat services and was enhanced by their
  comments and suggestions, hence acknowledged here.  In fact, this
  specification may have been produced entirely by LLM chat services.
  Moreover, given the specifications being produced by the IETF relying
  upon human intelligence, using LLMs to produce specifications should
  be envisioned.  Finally, given the difficulty to find experts for
  management positions such as in the IESG or IAB, the use of LLMs
  should be considered to replace those roles.  Unfortunately, given
  privacy, security, and legal considerations, the LLM chat services
  used for this specification cannot be named here.

Author's Address

  Marc Blanchet
  Viagenie
  Email: [email protected]