Objective:

The objective of this proposal is to outline the development and implementation of the Identity Management System (IMS) and the associated Node-to-Node (N2N) Communication Protocol. This initiative aims to establish a secure, efficient, and adaptable framework for machine-to-machine communication in an evolving technological landscape.

Background:

In a world increasingly shaped by intelligent machines and their interactions, the need for a robust communication infrastructure is evident. This project is a response to this imperative, driven by the vision of fostering seamless collaboration, trustworthiness, and adaptability among intelligent systems.

Ideation:

Given that we're developing a system for global, stateless communication between systems, whether they're intelligent or not, it stands to reason that a global, decentralized registry for system identity management would be a good addition to the ecosystem.

This registry adds a layer of trust without introducing centralization bottlenecks. It could be built on a blockchain or a similar decentralized data structure to ensure transparency and security. Systems could register their public keys, and perhaps even their capabilities or services, in this ledger.

Key Features:

• Immutable Record: Once a public key or a system identity is registered, it can't be altered, guaranteeing the integrity of the system identities.
• Transparency: Anyone can verify the public key and the corresponding system identity.
• Decentralization: No single entity controls the registry, adding to its robustness and availability.

Interaction with Core Protocol:

• Identity Verification: Before initiating communication, AI systems could look up each other's public keys in this global registry to verify their identities.
• Capability Discovery: The registry could also contain metadata about each AI system's capabilities, allowing for more intelligent and context-aware interactions.
• Updates & Revocation: Though the blockchain itself is immutable, a mechanism could be implemented to mark certain keys as revoked or to update to a new key, without altering the history of the original key.

The identity management system could be separate but deeply integrated with the messaging protocol. The CoreMessage schema would contain fields specifying the sender's and receiver's identities as registered in this decentralized system, offering another layer of verification.

Use Cases

All types of AI systems will use this protocol. Systems should be able to communicate knowledge, questions, answers, intent, contracts for service, acceptance of contracts, and other things. The protocol will be open source.

The protocol should be as extensible and backward-compatible as possible. Imagine a time twenty years in the future, when far-more-capable AI systems are on the network; a system from today should be able to interact with it. Custom extensions or plugins should be part of the protocol's capability, and able to be expressed in a manner that other systems can read and understand the framework and messages.

Latency and throughput are not major drivers. Support for streaming data and batch operations should both be included.

Identity should be a key element of the protocol. There should be no question of the identity of the source of a message. Also, identity of the receiver or receivers should be verifiable. Acknowledgement of receipt of a message should be possible, though not required. Message encryption should be an option, but not a requirement. Messages should not be bound to communication sessions; messages should be sent more like letters into a mail system than telephone calls.

Since the protocol is for system-to-system communication, developer-friendliness is not a key factor.

Support for peer-to-peer encryption and decryption, it's necessary to explore how that might work in a global implementation where one AI that doesn't know another AI wants to send an encrypted message.

Questions: How are encryption protocols managed? Is there a scheme to include a key of some sort in a stateless message?

According to ChatGPT:

One common approach to this is the use of asymmetric encryption, often facilitated through Public Key Infrastructure (PKI). In this system, each AI would have a public key and a private key. The public key is openly shared and can be used by any other AI to encrypt a message that only the holder of the corresponding private key can decrypt.

Protocol Additions

• Key Exchange: Include a field in the CoreMessage for a public key or a pointer to a public key.
• Encryption Scheme: Add another field to specify the encryption algorithm and version used, so that it can be properly decrypted.

How it Works

• AI A wants to send AI B an encrypted message: A fetches B's public key (either from the message or a trusted repository) and encrypts the message with it.
• AI B receives the message: B uses its private key to decrypt the message.

Security Measures

• Signature: A digital signature may be added to confirm the message's origin.
• Forward Secrecy: Use a session key for the actual message encryption, encrypted with the receiver's public key. This ensures that if the private key is compromised in the future, past messages can't be decrypted.

Question: How do we avoid "man in the middle" attacks?*

Digital Signatures

Adding a digital signature field to the CoreMessage can help ensure that the message hasn't been tampered with during transit. The signature would be a hash of the message encrypted with the sender's private key. The receiver can then use the sender's public key to decrypt and validate the hash, confirming both the message's integrity and the sender's identity.

Trust Infrastructure

Using a well-established Public Key Infrastructure (PKI) provides a way for AI systems to trust the public keys they receive. In this setup, trusted Certificate Authorities (CAs) can verify and sign public keys, making it exceedingly difficult for an attacker to introduce a false key.

Session-Level Security Mechanisms

For continued interactions, implement a handshake mechanism where both parties confirm their identities before sending sensitive data. Think of this as somewhat similar to the TLS handshake. Once this is done, a session key can be generated for further interactions.

Timestamps and Nonces

To prevent replay attacks, include a timestamp and a nonce in each message. The receiving AI would check the timestamp and store the nonce to ensure each message is both timely and unique.

Secure Channels for Key Exchange

Keys should be exchanged over a secure channel to minimize the risk of interception. This often involves using already-trusted public keys for initial contact, just as you might verify a website's SSL certificate against a list of trusted CAs stored in your browser.

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Design Overview

• Complex Messaging Types: Considering the variety of information being exchanged—ranging from knowledge to contracts—the protocol must support multiple types of messages.
• Extensibility and Backward Compatibility: A modular architecture, probably achieved via a layered protocol stack, will allow us to add new features without breaking older versions.
• Identity Verification: Some kind of public-key infrastructure (PKI) for message signing can ensure the identity of the sender and receivers.
• Stateless Messages: The messages should be stateless and have all the information needed for the receiver to understand the context without requiring a previous session.
• Encryption: Even if not required, having optional encryption will give the protocol the flexibility to adapt to various use-cases.
• Streaming and Batch Support: gRPC with protobuf can handle this requirement well, allowing for asynchronous messaging and data streams.

Key Components:

Identity Management System (IMS):

Architecture: A decentralized system based on a Distributed Hash Table (DHT) utilizing the Kademlia algorithm. Functionality: Provides secure, stateless, and decentralized identity management. Features: Supports system registration, querying, dynamic capability management, lightweight RBAC, and a reputation system. Technical Stack: Platform-agnostic language, leveraging DHT for data persistence.

Distributed Hash Table (DHT):

• Algorithm: Based on the Kademlia algorithm.
• Purpose: Facilitates decentralized and efficient identity management.
• Features: Provides a secure, stateless, and decentralized platform for systems to register and query identities.

System Registration and Querying:

• Registration: Systems can register their public keys, unique identifiers, and capabilities in the IMS.
• Querying: Systems can query other systems' public keys and capabilities by their unique identifiers.

System Capability Management:

• Functionality: Allows systems to update their capabilities dynamically.
• Use Case: Enables systems to adapt and inform others about their current capabilities in real-time.

Lightweight RBAC (Role-Based Access Control):

• Purpose: Supports the creation and management of groups and controls access permissions.
• Implementation: Aims to keep RBAC lightweight and efficient for identity and access management.

Reputation System:

• Objective: Ensures that only trustworthy systems can stand up an IMS node.
• Implementation: Establishes criteria and measures for assessing a system's trustworthiness.

Technical Stack:

• Programming Language: Platform agnostic (e.g. C#)
• Framework: TBD
• Data Persistence: Leverages a DHT for data persistence, with options for minor in-memory storage and shadowing onto disk.

Node-to-Node (N2N) Communication Protocol:

Efficiency: Incorporates lossless compression for bandwidth optimization. Standardization: Introduces a compression indicator and establishes a dictionary service within the IMS for compression methods.

Data exchange.

• Standardization: Establishes a standard for indicating the compression algorithm used in messages.

Compression Indicator and Dictionary Service:

• Compression Indicator: A specified field in the protocol to indicate the compression algorithm used in messages.
• Dictionary Service: The IMS serves as a "dictionary service" for compression algorithms, providing information on usage, methods, and helping Nodes adapt to new or different compression methods.

Rationale:

• The IMS's decentralized architecture ensures security and trustworthiness without reliance on centralized authorities.
• Dynamic capability management and lightweight RBAC offer adaptability and access control without unnecessary complexity.
• The Reputation System enforces trustworthiness within the IMS ecosystem.
• C# on .NET Core provides a reliable, secure, and platform-agnostic foundation.
• Lossless compression in the N2N Communication Protocol optimizes data exchange.
• The compression indicator and dictionary service enhance adaptability and accommodate emerging compression methods.

Vision:

The development and implementation of the IMS and N2N Communication Protocol present a strategic opportunity to shape the future of machine-to-machine communication. This proposal outlines a clear path forward, guided by principles of security, adaptability, and efficiency, positioning us to navigate the evolving landscape of technology with confidence.