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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
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
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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: marc.blanchet@viagenie.ca