Distributed Ledger Mass Balancing via Secret Sharing
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Solution Overview
Problem
Publicly verifiable mass balancing protocols on distributed ledgers lack privacy, potentially harming producers' competitive advantages and conflicting with legal regulations like GDPR, as they reveal sensitive production details.
Innovation Solution
Implementing an asymmetric cryptosystem and additive secret sharing to compute and store random shares of production amounts on a secure, distributed ledger, ensuring privacy while maintaining public verifiability through blinded amounts and encrypted transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If production amounts are stored publicly on a distributed ledger for mass balancing verification, then public verifiability is improved, but privacy of production details deteriorates
Solution Approach 1:
The patent segments production amounts into multiple additive shares (x1, x2, ..., xn) where each share is stored on the distributed ledger. Individually, each share reveals no information about the total production amount, but collectively they enable public verification when summed. This segmentation resolves the contradiction by dividing the sensitive information into non-sensitive components.
Solution Approach 2:
The patent introduces random values (r1, r2, ..., rn) as intermediaries that are added to each production share before storage. These random values act as mediators that mask the actual production amounts while allowing verification through cryptographic proofs. The random values are later removed or accounted for during verification, enabling public verification without exposing private production details.
2Loss of information
If individual production amounts are made visible on the distributed ledger, then transparency is improved, but competitive advantage deteriorates
Solution Approach 1:
By segmenting the total production amount into multiple additive shares stored on the ledger, the system achieves transparency in aggregate production verification while keeping individual component values hidden. Competitors can verify total production compliance but cannot infer individual production details that would reveal competitive strategies or capabilities.
Solution Approach 2:
The patent applies different quality levels to different parts of the data: aggregate production data is made transparent and verifiable, while individual production amount details remain private. This local differentiation of information quality allows transparency where needed for verification while protecting competitive-sensitive details.
3Ease of operation
If customer data is stored in a distributed ledger for verification, then public access is improved, but legal compliance deteriorates
Solution Approach 1:
The patent segments customer-related production data into additive shares that can be publicly accessed and verified on the distributed ledger. Each individual share contains no identifiable customer information, but the sum enables verification of production claims. This segmentation allows public access for verification while maintaining legal compliance with data protection regulations.
Solution Approach 2:
The patent uses cryptographic intermediaries and zero-knowledge proof mechanisms that allow public verification of production data without exposing underlying customer information. These intermediaries enable ease of public access for verification purposes while ensuring legal compliance by preventing direct access to sensitive customer data.
Data Source
AI summary
A producer may supply amounts xi of a good to a plurality of consumers Ci in a series of transactions and be subject to a mass balancing verification protocol after every K transactions. A producer platform may compute K random shares (r1 through rK) of a random value r, publish blinded amounts ti representing xi+ri to a secure, distributed transaction ledger, and transmit an encrypted ri to consumer Ci using an asymmetric cryptosystem. A consumer platform may receive and decrypt ri (while the consumer Ci actually receives an amount {circumflex over (x)}i of the good from the producer), compute {circumflex over (x)}i+ri and generate a fraud alert signal if it differs from the published ti. The consumer platform may also transmit an encrypted rolling sum value to a next consumer Ci+1. A verifier platform may, after K transactions, execute the mass balance verification protocol to determine a total amount of the good that the producer had collectively supplied to the consumers Ci. The verifier platform may also generate a fraud alert signal when appropriate based on the total amount and a maximum allowed amount.