Introduction
This proposal addresses the challenge of Sybil attacks by introducing a practical solution for ensuring the uniqueness of identity (ID) within the Concordium Node without altering the existing ID credentials scheme. By leveraging Zero-Knowledge Proofs (ZKPs) and context-dependent identifiers generated using the Concordium node, we can maintain privacy, security, and regulatory compliance while ensuring robust Sybil resistance.
This proposal also addresses handling legacy users, cryptographic considerations, scaling, user consent, and error handling to ensure a comprehensive solution.
Conceptual Approach
Use of Pseudo-Random Function Family (PRF) for Context-Dependent Identifiers
Objective: Use a secure PRF to generate context-dependent identifiers (CUIDs) within the Concordium node, ensuring each user has a unique ID across different services without revealing their actual identity.
- Generation of Uniqueness Key (UK) by the Node:
- The node generates a uniqueness key (UK) for each user upon their first interaction.
- This UK is derived using a secure cryptographic function based on user attributes, ensuring it remains consistent and unique.
- Context-Dependent Identifier Generation:
- When a user signs up for a service, the node generates a context-specific identifier (CUID) using the UK and the service context.
- Users provide a ZKP to prove that the CUID was generated correctly without revealing the UK or underlying identity attributes.
- Distribution and Storage of Uniqueness Key (UK):
- The UK is stored locally in the node’s database.
- The UK is synchronized across nodes to ensure consistency and accessibility.
Technical Implementation
1. Generation of Uniqueness Key (UK) by the Node
Process:
- Upon the user’s first interaction, the Concordium node generates a UK using a secure cryptographic function (e.g., PRF).
- This UK is derived from user attributes (e.g., hash of user ID credential components) and stored securely in the node’s database.
- The UK ensures uniqueness without changing the existing ID credentials scheme.
fn generate_uk(user_id: &UserId) -> UniquenessKey {
let input_data = format!("{:?}", user_id);
let hashed_data = hash_function(&input_data);
let uniqueness_key = prf(hashed_data);
uniqueness_key
}
2. Context-Dependent Identifiers (CUIDs)
Functionality:
- Users generate context-specific identifiers (CUIDs) using their UK and the service context.
- These identifiers prevent tracking across services by ensuring the same user produces different identifiers for different contexts.
- The use of ZKPs ensures that the identifier can be validated without exposing the UK or underlying identity attributes.
fn generate_cuid(uk: &UniquenessKey, context: &str) -> ContextualUid {
let input_data = format!("{:?}{:?}", uk, context);
let cuid = prf(input_data);
cuid
}
3. Distribution and Synchronization of Uniqueness Key (UK)
UK Storage and Sync:
- Local Storage: The UK is stored securely in the local node database.
- Synchronization: The UK must be synchronized across all participating nodes to ensure consistency and prevent duplicates.
async fn store_uk_async(user_id: &UserId, uk: &UniquenessKey) -> Result<(), StorageError> {
db.put_async(user_id, serialize(uk)?).await?;
Ok(())
}
async fn sync_uk_across_nodes(uk: &UniquenessKey) -> Result<(), NetworkError> {
let message = NetworkMessage::UKUpdate(uk.clone());
network.broadcast_async(message).await?;
Ok(())
}
4. Integration in Node Operations
Node Startup Logic:
- Ensure the node handles the generation and verification of CUIDs upon service sign-up.
#[tokio::main]
async fn main() -> Result<(), Box<dyn Error>> {
// Node initialization...
if let Some(url_arg) = env::args().find(|arg| arg.starts_with("--hotsync-url=")) {
let url = url_arg.split('=').nth(1).expect("Missing URL for --hotsync-url flag");
hotsync_async(url).await?;
}
// Start the Concordium node
}
Database Handling for CUIDs:
- Convert storage and retrieval functions for CUIDs to asynchronous operations.
async fn store_cuid_async(context: &str, cuid: &ContextualUid) -> Result<(), StorageError> {
db.put_async(context, serialize(cuid)?).await?;
Ok(())
}
async fn retrieve_cuid_async(context: &str) -> Result<ContextualUid, StorageError> {
let encoded_cuid = db.get_async(context).await?;
Ok(deserialize(&encoded_cuid)?)
}
Network Communication for CUIDs:
async fn send_cuid_async(cuid: &ContextualUid, to_node: &NodeId) -> Result<(), NetworkError> {
let message = NetworkMessage::CUID(cuid.clone());
network.send_async(to_node, message).await?;
Ok(())
}
async fn receive_cuid_async(message: NetworkMessage) -> Result<(), NetworkError> {
match message {
NetworkMessage::CUID(cuid) => {
process_cuid_async(cuid).await?;
},
_ => {},
}
Ok(())
}
Handling Legacy Users Without UK
Process:
- During the next interaction with the system, check if a user has a UK.
- If not, automatically generate a UK and notify the user if required.
async fn check_and_generate_uk(user_id: &UserId) -> Result<UniquenessKey, StorageError> {
match db.get_async(user_id).await {
Ok(existing_uk) => Ok(existing_uk),
Err(_) => {
let new_uk = generate_uk(user_id);
db.put_async(user_id, serialize(new_uk)?).await?;
sync_uk_across_nodes(&new_uk).await?;
// Notify user if necessary
Ok(new_uk)
}
}
}
Cryptographic Considerations
- Compatibility: Ensure the chosen PRF and hashing functions (e.g., Pedersen Hash) are compatible with Concordium’s cryptographic framework and offer robust security.
- Integration: Ensure the cryptographic library is fully integrated into the Concordium node without significant performance trade-offs.
Scaling Considerations
Benchmarking:
- Benchmark node performance under stress to avoid bottlenecks.
- Ensure async processing helps handle the additional load of generating and verifying CUIDs.
fn benchmark_cuid_generation() {
// Code to measure the performance of CUID generation
}
fn benchmark_zkp_verification() {
// Code to measure the performance of ZKP verification
}
User Consent and Transparency
User Communication:
- Inform users about how their uniqueness is generated and used.
- Ensure compliance with regulatory laws and best practices.
async fn inform_user_about_uk(user_id: &UserId) {
// Code to send a notification to the user
}
Error Handling and Recovery
Error Handling:
- Implement robust error handling for potential issues like failed UK generation or ZKP verification.
async fn handle_errors() -> Result<(), CustomError> {
// Code to handle errors and implement recovery mechanisms
}
Recovery Scenarios:
- Plan for recovery in case of network failures, incomplete transactions, or miscommunication between nodes.
async fn recovery_scenario() -> Result<(), CustomError> {
// Code to handle recovery
}
Privacy & Compliance
When implementing the Uniqueness Key (UK) in Concordium Node, privacy considerations are essential to ensure that the solution aligns with privacy regulations (such as GDPR) and meets the needs of users who value privacy. Storing the UK in the node can potentially raise some concerns. Let’s break down the privacy aspects of using a UK stored in the node:
1. Data Minimization
- Concern: Storing any form of user-identifiable data, even in hashed or pseudonymous form, could introduce risks if that data is not adequately protected or if more data is stored than necessary.
- Mitigation: The UK itself should only store the minimum required data for uniqueness. The UK can be derived from user attributes using a secure, non-reversible cryptographic function, ensuring that the original identity data is not stored in the node.
- For example, only using hashed versions of user attributes means that even if the UK is accessed, it cannot be used to derive the original user information.
2. Potential for Linkability
- Concern: If a UK is used across multiple services, or if the same UK is stored on multiple nodes, there’s a risk that users could be tracked or linked across different contexts.
- Mitigation: By using context-dependent identifiers (CUIDs), the risk of linkability is reduced. Each service or context would generate a unique CUID from the UK, ensuring that even though the same UK is stored in the node, the CUIDs are different across services. This prevents cross-service tracking while preserving the uniqueness of the ID within each context.
- Zero-Knowledge Proofs (ZKPs) should be used to prove the validity of CUIDs without revealing the UK or underlying user identity.
3. Data Breach and Security Risks
- Concern: If the node or its database is compromised, attackers might gain access to the UK. If the UK is not adequately protected, this could lead to security breaches or unauthorized use of the UK.
- Mitigation: To address this, the UK should be cryptographically protected (e.g., encrypted) at rest and in transit. Additionally, the UK itself should be derived using a one-way cryptographic function (like a Pedersen hash or another PRF). This ensures that the UK is secure and cannot be reverse-engineered to reveal original identity attributes, even if the UK is exposed.
4. Decentralization and Trust
- Concern: Centralized storage of the UK within a node could be seen as a privacy risk, as it relies on the integrity of the node operator. Users might feel that their data is not fully decentralized or trustless.
- Mitigation: To mitigate this, Concordium could decentralize the storage and management of the UK by ensuring that the UK is only generated and stored on first-party nodes operated by trusted validators. In addition, cryptographic measures, such as ZKPs, ensure that nodes do not have access to the underlying identity data and only store the UK in a non-reversible format.
- Further decentralization can be achieved by allowing users or IDPs to generate their own UK, keeping the node’s role limited to verifying the ZKPs without having to store any identity-related data.
5. Compliance with GDPR and Other Privacy Regulations
- Concern: GDPR and similar privacy regulations emphasize data protection and the right of individuals to control their personal data. Storing any form of unique identifier related to a user may be seen as processing personal data.
- Mitigation: To comply with GDPR:
- Pseudonymization: The UK should be considered a pseudonymous identifier. It must not allow direct identification of users, and it must be stored in a way that ensures it cannot be linked back to any specific individual without additional data.
- User Consent: Users should be informed that a UK is generated and stored. Consent mechanisms could be introduced where users are made aware of how their uniqueness is managed and what data is stored in the node.
- Data Subject Rights: Users should have the ability to review, request deletion, or correct their UK if necessary, in line with GDPR’s data subject rights (though in the case of cryptographically derived keys, this process may be abstract).
6. Retention and Purpose Limitation
- Concern: How long will the UK be stored in the node, and for what purpose? Storing data indefinitely could pose privacy risks.
- Mitigation: Retention policies should be implemented where the UK is stored only as long as necessary. Nodes should have clear policies for retention and automatic deletion of UKs when they are no longer needed for a specific context.
- Purpose limitation: The UK should only be used for the purpose of ensuring uniqueness and Sybil resistance and not for any other purpose, such as tracking or profiling users.
7. Audit and Transparency
- Concern: Users might be concerned about how their data (including the UK) is handled within the node.
- Mitigation: Provide audit mechanisms and transparency reports to allow users to understand how their UK is being stored, used, and protected. These reports could be anonymized and cryptographically verified to show that the node is adhering to best practices without exposing user data.
Final Summary on Compliance
Storing the Uniqueness Key (UK) in the Concordium node introduces privacy risks, but these can be effectively mitigated with thoughtful design and strong cryptographic protections. By implementing context-dependent identifiers, pseudonymization, encryption, and Zero-Knowledge Proofs (ZKPs), Concordium can ensure that the UK system enhances Sybil resistance while safeguarding user privacy.
Key considerations:
- The UK must be non-reversible and protected at all times, ensuring that it cannot be traced back to the original identity data.
- Users must not be trackable across different services, with context-dependent identifiers (CUIDs) ensuring that identifiers are unique for each service.
- Transparency, user consent, and strict compliance with privacy regulations (such as GDPR) must be guaranteed, particularly in regions with stringent data protection laws.
By adhering to these principles, the UK system can maintain both privacy and security while effectively preventing Sybil attacks.
Final Summary on Proposal
This proposal offers a practical and privacy-preserving solution to Sybil attacks by introducing context-dependent identifiers and ensuring robust uniqueness of IDs within the Concordium Node. By leveraging a secure generation of the Uniqueness Key (UK) and integrating it with context-dependent identifiers (CUIDs) and Zero-Knowledge Proofs (ZKPs), the system achieves both privacy protection and regulatory compliance without altering the existing ID credential scheme.
Key Benefits:
- Sybil Resistance: Enhanced protection against duplicate identities across multiple services.
- Privacy Protection: ZKPs ensure that user privacy is maintained without exposing sensitive data, even during verification.
- Seamless User Experience: The system integrates smoothly into existing infrastructures without requiring additional dApps or manual interventions by the user.
- Comprehensive Handling: It addresses legacy users, cryptographic requirements, scaling, user consent, and robust error handling mechanisms.
It is recommended that Concordium’s tech & science teams prioritize implementing these improvements to bolster the network’s scalability and security, while addressing the core issue of identity uniqueness in a user-friendly and privacy-compliant manner. Additionally, this solution can be extended towards seamless identity verification utilizing the Uniqueness Key (UK).
I look forward to inputs and hope that we can move forward with this model as it resolves the mentioned potential problems from earlier proposals, however we do need to finalize the low level detail and implement it, but this is a model that can be done with very little effort and with a huge gain however finalizing the details in the technical implementation to be compliant is essential and must be in focus for the final implementated model.
For further details on the enhancements related to asynchronous ZKP handling and its impact on TPS and scalability, please refer to the previously submitted proposal.