Zero-Knowledge Contact Tracing Blockchain Privacy
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Solution Overview
Problem
Digital contact tracing applications face accuracy, security, and privacy concerns due to vulnerabilities such as man-in-the-middle attacks, interception, and privacy breaches, particularly in the context of COVID-19 contact tracing.
Innovation Solution
A non-interactive zero-knowledge crowd verifiable digital contact tracing method using a blockchain network with ZK-SNARK cryptographic protocol, which enables secure and private data exchange by generating and verifying proofs without revealing user identities or sensitive information, ensuring transparency and tamper-proof storage on a public ledger.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized data storage and processing is used in contact tracing applications, then contact tracing efficiency and speed are improved, but user privacy and security are compromised due to centralized vulnerability to attacks and breaches
Solution Approach 1:
The patent segments the centralized contact tracing system into distributed components: multiple blockchain nodes instead of a single central server, distributed verification instead of centralized validation. This segmentation eliminates the single point of failure while maintaining tracing efficiency through parallel processing across the network.
Solution Approach 2:
The patent introduces cryptographic intermediaries (zero-knowledge proofs, digital signatures, hashed identifiers) that mediate between data collection and verification. These cryptographic layers enable efficient contact tracing while protecting user privacy by allowing verification without exposing sensitive information.
2Measurement precision
If user identities and location histories are stored in a centralized repository, then contact tracing accuracy is improved, but privacy breaches occur due to tracking and potential data exposure
Solution Approach 1:
The patent extracts identifying information from the contact tracing data structure. User identities and sensitive personal information are removed and replaced with cryptographic identifiers (hashed values, anonymous keys). The system retains tracing accuracy through these pseudonymous identifiers while eliminating the privacy breach vector of storing actual identities.
Solution Approach 2:
The patent transforms sensitive parameters (user identities, exact locations) into cryptographic parameters (hashed identifiers, proximity proofs). This parameter transformation maintains the functional capability to trace contacts while changing the nature of stored data from personally identifiable to anonymous cryptographic representations.
3Reliability
If digital contact tracing systems collect and store detailed contact information, then contact tracing capability is improved, but the system becomes vulnerable to man-in-the-middle attacks, interception, and spoofing
Solution Approach 1:
The patent applies preliminary cryptographic actions to contact tracing data before storage or transmission. Digital signatures are applied to verify data authenticity, and zero-knowledge proofs are generated in advance to prove contact occurrence without revealing sensitive information. This preliminary cryptographic processing prevents man-in-the-middle attacks and spoofing while maintaining tracing capability.
Solution Approach 2:
The patent replaces mechanical/trust-based verification systems with cryptographic verification. Instead of relying on centralized authority or manual verification, the system uses cryptographic proofs and digital signatures to automatically verify contact data authenticity, eliminating vulnerabilities to interception and spoofing attacks.
4Object-affected harmful factors
If randomized MAC addresses are used to conceal user identities, then some privacy protection is achieved, but location histories can still be tracked through centralized repositories
Solution Approach 1:
The patent uses cryptographic copying where anonymous identifiers are created as cryptographic representations of contact events. Instead of storing actual location histories, the system stores cryptographic proofs of proximity events. These cryptographic copies verify contact occurrence without revealing traceable location information, preventing both identity disclosure and location tracking.
Data Source
AI summary
A method of non-interactive zero-knowledge crowd verifiable digital contact tracing, system and devices that provides improved accuracy and/or privacy by improving the validity of digital contact tracing sources. Private information associated with a respective user intended for a receiver is uploaded to a data server. The receiver is notified that the private information has been uploaded to the data server. A proof of the private information is generated using a proof function of a non-interactive zero-knowledge cryptographic protocol and added to a contact tracing blockchain for the respective user. A second blockchain transaction is added in response to verification of the proof by a verifier network using a verification function of the non-interactive zero-knowledge cryptographic protocol and the receiver is be notified.