Privacy preservation in private consensus networks
Implementations of the present disclosure include determining that a private transaction is to be recorded in a distributed ledger system (DLS) based on a consensus protocol executed by a set of entities participating in the DLS, the private transaction including a transaction between a subset of entities of the set of entities, providing a set of noisy transactions based on a transaction model, and transmitting data representative of at least a portion of the private transaction, and data representative of each noisy transaction in the set of noisy transactions for recording in the DLS based on the consensus protocol.
1. A computer-implemented method executed by at least one processor, the method comprising:
determining, by the at least one processor, that a private transaction is to be recorded in a distributed ledger system (DLS) based on a consensus protocol executed by a set of entities participating in the DLS, the private transaction comprising a transaction between a subset of entities of the set of entities;
providing, by the at least one processor, a set of noisy transactions based on a transaction model; and
transmitting, by the at least one processor, data representative of at least a portion of the private transaction, and data representative of each noisy transaction in the set of noisy transactions for recording in the DLS based on the consensus protocol.
2. The method of claim 1 , further comprising determining a number of noisy transactions to be generated for the set of noisy transactions based on a signal-to-noise ratio.
3. The method of claim 2 , wherein the signal-to-noise ratio is determined for a current settlement period, and is based on a statistical value of private transactions across multiple settlement periods, and a statistical value of noisy transactions across the multiple settlement periods.
4. The method of claim 1 , further comprising calculating an identifier assigned to the private transaction based on a hash function, and a secret nonce value that is shared between entities in the subset of entities.
5. The method of claim 1 , wherein the transaction model is representative of one or more features of historical transaction data representative of transactions between entities in the subset of entities.
6. The method of claim 1 , wherein the DLS comprises a consortium DLS.
7. The method of claim 1 , wherein the private transaction, noisy transactions in the set of noisy transactions, and a plurality of public transactions are recorded in the DLS based on the consensus protocol.
8. One or more non-transitory computer-readable storage media coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
determining that a private transaction is to be recorded in a distributed ledger system (DLS) based on a consensus protocol executed by a set of entities participating in the DLS, the private transaction comprising a transaction between a subset of entities of the set of entities;
providing a set of noisy transactions based on a transaction model; and
transmitting data representative of at least a portion of the private transaction, and data representative of each noisy transaction in the set of noisy transactions for recording in the DLS based on the consensus protocol.
9. The one or more non-transitory computer-readable storage media of claim 8 , wherein the operations further comprise: determining a number of noisy transactions to be generated for the set of noisy transactions based on a signal-to-noise ratio.
10. The one or more non-transitory computer-readable storage media of claim 9 , wherein the signal-to-noise ratio is determined for a current settlement period, and is based on a statistical value of private transactions across multiple settlement periods, and a statistical value of noisy transactions across the multiple settlement periods.
11. The one or more non-transitory computer-readable storage media of claim 8 , wherein the operations further comprise: calculating an identifier assigned to the private transaction based on a hash function, and a secret nonce value that is shared between entities in the subset of entities.
12. The one or more non-transitory computer-readable storage media of claim 8 , wherein the transaction model is representative of one or more features of historical transaction data representative of transactions between entities in the subset of entities.
13. The one or more non-transitory computer-readable storage media of claim 8 , wherein the DLS comprises a consortium DLS.
14. The one or more non-transitory computer-readable storage media of claim 8 , wherein the private transaction, noisy transactions in the set of noisy transactions, and a plurality of public transactions are recorded in the DLS based on the consensus protocol.
15. A system, comprising:
a computing device; and
a computer-readable storage device coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations comprising:
determining that a private transaction is to be recorded in a distributed ledger system (DLS) based on a consensus protocol executed by a set of entities participating in the DLS, the private transaction comprising a transaction between a subset of entities of the set of entities;
providing a set of noisy transactions based on a transaction model; and
transmitting data representative of at least a portion of the private transaction, and data representative of each noisy transaction in the set of noisy transactions for recording in the DLS based on the consensus protocol.
16. The system of claim 15 , wherein the operations further comprise: determining a number of noisy transactions to be generated for the set of noisy transactions based on a signal-to-noise ratio.
17. The system of claim 16 , wherein the signal-to-noise ratio is determined for a current settlement period, and is based on a statistical value of private transactions across multiple settlement periods, and a statistical value of noisy transactions across the multiple settlement periods.
18. The system of claim 15 , wherein the operations further comprise: calculating an identifier assigned to the private transaction based on a hash function, and a secret nonce value that is shared between entities in the subset of entities.
19. The system of claim 15 , wherein the transaction model is representative of one or more features of historical transaction data representative of transactions between entities in the subset of entities.
20. The system of claim 15 , wherein the DLS comprises a consortium DLS.