The instant disclosure illustrates how the privacy and security of activities occurring on distributed ledger-based networks (DLNs) can be enhanced with the use of zero-knowledge proofs (ZKPs) that can be used to verify the validity of at least some aspects of the activities without private information related to the activities necessarily being revealed publicly. Methods and systems that are directed at facilitating the tracking and recovery of assets stolen on ZKP-enabled DLNs while preserving the confidentiality of the tokens are presented herein.

A method of generating a deniable commitment of personal data of a user with an unlinkable proof of the commitment of the personal data for securing user privacy in a digital identity system includes receiving the personal data of the user and receiving the commitment of the personal data according to a commitment scheme. An interactive zero-knowledge proof is engaged in with the user so as to verify that the commitment of the personal data opens to the personal data of the user.

In another aspect, a system for machine learning using a distributed framework, includes a computing device communicatively connected to a plurality of remote devices, the computing device designed and configured to select at least a remote device of a plurality of remote devices, determine a confidence level of the at least a remote device, and assign at least a machine-learning task to the at least a remote device, wherein assigning further comprises assigning at least a secure data storage task to the at least a remote device and assigning at least a model-generation task to the at least a remote device.

A system for an artificial intelligence synchronized distributed ledger. The system includes a computing device containing a receiving module, the receiving module designed and configured to receive an input from a remote device, parse the input to identify protected and non-protected data contained within the input, transform the protected data into a digitally signed assertion and convert the non-protected into an encrypted datastore. The computing device containing a processing module, the processing module designed and configured to receive the digitally signed assertion from the receiving module, insert the digitally signed assertion into an immutable sequential data structure, receive the encrypted datastore, retrieve at least an input, generate a record utilizing the at least a retrieved input, and perform a first machine-learning process utilizing the at least a retrieved input.

A system and a method for digital proof generation are provided. The system includes a data management module to manage dataset having plurality of data rows and a query execution and verification module including a commitment storage sub-module, a query execution sub-module and a result verification sub-module. The data management module receives query from the query execution sub-module, related to operation on data rows of plurality of data rows, which is processed to generate execution result associated with data rows. The execution result is transferred along with data rows to the query execution sub-module. A set of commitments associated with execution result is transferred to the commitment storage sub-module. The query execution sub-module transfers set of commitments, from the commitment storage sub-module, and data rows to the result verification sub-module for verification, and receives a verification result from the result verification sub-module.

An apparatus for digital posting match recommendation and corresponding methods are provided. An exemplary apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory includes instructions configuring the at least a processor to receive a posting datum of a posting, receive a user datum from a user, retrieve a plurality of records from an immutable sequential listing, determine a compatibility score as a function of the posting datum and the user datum, determine a record recommendation as a function of the posting datum, the user datum, and the plurality of records and display, at a display communicatively connected to the at least a processor, the revised record recommendation and the compatibility score to the user.

Disclosed is a zero-knowledge distributed application configured to securely share information among groups of users having various roles, such as doctors and patients. Confidential information may be encrypted client-side, with private keys that reside solely client side. Encrypted collections of data may be uploaded to, and hosted by, a server that does not have access to keys suitable to decrypt the data. Other users may retrieve encrypted data from the server and decrypt some or all of the data with keys suitable to gain access to at least part of the encrypted data. The system includes a key hierarchy with multiple entry points to a top layer by which access is selectively granted to various users and keys may be recovered.

A method and system for blockchain-driven communication using encapsulated virtual chains can facilitate blockchain-driven inter-PSAP communication using encapsulated virtual chains. Embodiments can be generalized for any context (e.g. not only for the specific examples of the Next Generation 9-1-1 and 1-1-2 (NG9-1-1/NG1-1-2) architectures).

An authentication method of a prover by a verifier includes: performing at least once, an enrollment process by an enrollment center computer; and subsequent to performing the enrollment process, performing an on demand authentication process including: receiving at a verifier computer from the prover, a prover authentication request sent from the prover computer device which includes the prover identity and a preferred ZKP protocol identifier; looking up a prover's public key in the database via the identity; the verifier sending a selected ZKP protocol identifier to the prover computer device; commencing a round of authentication by receiving a commitment generated according to the selected ZKP protocol; and repeating the step of commencing a round of authentication until the verifier computer accepts or rejects the prover's identity. A zkMFA method of authentication and an authentication system for authenticating a prover by a verifier are also described.

A method to prove the safety (e.g., value-alignment) and other properties of artificial intelligence systems possessing general and/or super-human intelligence (together, AGI). The method uses probabilistic proofs in Interactive proof systems (IPS), in which a Verifier queries a computationally more powerful Prover and reduces the probability of the Prover deceiving the Verifier to any specified low probability (e.g., 2.sup.−100) IPS-based procedures can be used to test AGI behavior control systems that incorporate hard-coded ethics or valuelearning methods. An embodiment of the method, mapping the axioms and transformation rules of a behavior control system to a finite set of prime numbers, makes it possible to validate safe behavior via IPS number-theoretic methods. Other IPS embodiments can prove an unlimited number of AGI properties. Multi-prover IPS, program-checking IPS, and probabilistically checkable proofs extend the power of the paradigm. The method applies to value-alignment between future AGI generations of disparate power.