35 results about "Verified computing" patented technology

Various aspects of the disclosure relate to automated testing for application programming interfaces (APIs). A dynamic API validation computing system leverages a generative AI model to dynamically generate a multitude of data sets and rules for use during API validation activities. A federated byzantine agreement mechanism performs the validation of each API using the generated test cases and test data. A generator engine incorporates a generative AI model that may be trained on a large corpus of API metadata and / or data characteristics to predict data patterns and / or validation rules for each of the APIs under test. The generator engine may also predict a structure and format of requests based on the training model inputs. Multiple Test cases for an API created through use of the generative AI model may be distributed and executed on different testing nodes that reach a consensus about whether each API has passed or failed.

The invention is suitable for the technical field of data processing, and particularly relates to a financial data processing and classification method, system and equipment based on verifiable computing, and the method comprises the steps: obtaining on-chain transaction data verified by a block chain consensus node storage and risk-related index data verified by an under-chain oracle machine; the problems that the authenticity of traditional financial data is difficult to verify and the data is split are solved; calling a risk assessment model through an intelligent contract deployed on a block chain, and placing an assessment process in a decentralized block chain network; performing verifiable calculation through an intelligent contract to determine a total performance score and a risk index, and realizing whole-course tracing and verification of a calculation process by utilizing the characteristics of verifiable calculation of a block chain; the total performance score and the risk index are stored in the block chain as non-tampering records, and the risk rating groups are automatically divided according to the fixed rating rule on the chain through the smart contract, so that the authenticity, objectivity, verifiability and fairness of financial data processing are guaranteed.

An adaptive redundancy-scheduling system for column-oriented neural-network compute arrays is disclosed. The system periodically verifies correctness of compute columns through concurrent redundant-column execution and adjusts test intervals and substitution thresholds in response to observed error statistics. Redundant columns are activated only when measured fault probability exceeds a programmable confidence level, maintaining yield and reliability with minimal performance impact. Verification tasks occur during non-critical compute intervals, and error history is retained for long-term reliability prediction.

Mechanisms are provided to perform intelligent compliance verification for monitored computing environments. The mechanisms train a first artificial intelligence (AI) computer model to generate rules from natural language content, to thereby generate a first trained AI computer model. The mechanisms train a second AI computer model to verify compliance of a monitored computing environment with rules generated by the first AI computer model, to thereby generate a second trained AI computer model. The mechanisms receive a regulation electronic document that comprises natural language content describing a regulation and determining compliance of a monitored computing environment based on a processing of the regulation electronic document by the first trained AI computer model to generate a rule corresponding to the regulation electronic document, and application of the generated rule by the second trained AI computer model to verify compliance of the monitored computing environment.

The present application relates to the field of specific computing model and information security technology, aiming at the problems of high computing cost and high cost in existing outsourcing reasoning technology, a polynomial chain verification method and device for outsourcing neural network reasoning are proposed.The method comprises: data input;in the preprocessing stage, the client generates the mask matrix of the input data, the model end generates the mask and the verification auxiliary matrix of the model parameter, the input data, the mask matrix and the Beaver triple are divided into multiple shares and distributed to different computing servers;by constructing a verifiable polynomial chain, the verification amount and the mask are generated under additive secret sharing and returned to the client, and by designing a polynomial form of verification equation, the verification of the reasoning process is completed.The present application completes the reasoning verification by designing a polynomial equation, ensures the integrity of the whole process and the privacy, and realizes the low-overhead, low-cost step-level verification with constant-level online verification calculation time of parallel computing.

A computer-implemented method (600) and system (1) for verifying ownership of a computer software for installation using a distributed hash table (13) and a peer-to-peer distributed ledger (14). This may be the Bitcoin blockchain or an alternative blockchain implementation. The method includes determining (610) a second user public key associated with a second user (24) from a transaction record stored on the peer-to-peer distributed ledger (14). A second public key associated with the second user may be determined (620) from an entry on the distributed hash table (13). The method further includes comparing (630) the second user public key and the second public key, and verifying (640) the ownership of the computer software based on the comparing of the second user public key and the second public key.

The invention discloses a data contract strategy credible execution and traceability system and method, and relates to the technical field of computer information security and cryptography application, and the method comprises the following steps: strategy formalized compiling and circuit generation, key generation and security initialization, verifiable execution and proof generation, and differential privacy watermark generation and injection. Safe destruction and result return; the digital policy trusted execution and traceability system comprises a policy compiling module, a key management module, a verifiable calculation engine, a differential privacy watermark module, a security sandbox and destruction module and an audit traceability module. According to the method, the dependence on a specific hardware architecture is replaced by a cryptographic algorithm and a formalized verification method, so that the side channel attack risk, high cost and compatibility limitation existing in a hardware scheme are effectively overcome, and the deployment and operation and maintenance threshold of a trusted computing environment is remarkably reduced; and a universal trusted infrastructure is provided for a large-scale data circulation scene.

A computer-implemented method and system for verifying the integrity of a computer software for installation using a distributed hash table and a peer-to-peer distributed ledger. This may be the Bitcoin blockchain or an alternative implementation. The method includes determining a metadata associated with a transaction record stored on the peer-to-peer distributed ledger. An indication of an entry stored on the distributed hash table may be determined from the metadata. The method further includes determining a third hash value based on the computer software and determining a fourth hash value from the entry on the distributed hash table. The method further includes comparing the third hash value and the fourth hash value and verifying the integrity of the computer software based on the comparing of the third hash value and the fourth hash value.

Facilitating peer-to-peer cloud computing resource sharing with a licensed distributed ledger is provided. A request of a computing resource consumer for additional computing resources from a computing resource provider via a peer-to-peer decentralized network is detected. In response to verifying that the computing resource consumer is authorized to consume the additional computing resource and the computing resource provider is authorized to transfer the additional computing resource to the computing resource consumer via the peer-to-peer decentralized network, a computing resource exchange environment is generated to transfer the additional computing resource from the computing resource provider to the computing resource consumer. Additional computing resources are transferred from a computing resource provider to a computing resource consumer for consumption via a computing resource exchange environment. Additional computing resources provided by computing resource providers and consumption of the additional computing resources by computing resource consumers are anonymized.

A method includes steps performed by a first computing device provisioned with a unique device secret, UDS, of generating an N chained certificate(s) attesting the authenticity of an N set(s) of device-specific data of the first computing device, and transmitting the N chained certificate(s) to a second computing device. The step of generating the N chained certificate(s) includes a generation process that includes: deriving, using a key ladder, a key from the UDS, generating an authentication tag from a set of device-specific data, using the key, generating a certificate that includes the set of device-specific data and the authentication tag, encrypting the set of device-specific data with the key, and providing the encrypted set of device-specific data as an input to the key ladder for a subsequent generation process.

To provide a decentralized processing system, method and storage medium that are accompanied by decentralization of computation tasks to one or more untrusted worker computer systems.SOLUTION: In a method, when an untrusted worker computer system executes calculation for a request computer system, the request computer system (or another verification request computer system) provides information enabling the request computer system to cryptographically verify that the task is completed correctly, the worker computer system provides information including proof and I / O data after the calculation is completed, and the request computer system uses setting, proof and I / O data of open verification key parameters to verify that the calculation executed by the untrusted worker computer system is correct, the calculation executed by a worker being related to a block chain transactions.SELECTED DRAWING: Figure 2

The invention relates to the technical field of specific calculation models and information security, and provides an outsourcing neural network reasoning-oriented polynomial chain verification method and device aiming at the problems of high calculation overhead and high cost in the existing outsourcing reasoning technology. The method comprises the following steps of: inputting data; in the preprocessing stage, a client side generates a mask matrix of input data, a model side generates a mask of model parameters and a verification auxiliary matrix, and the input data, the mask matrix and a Beaver triple are divided into a plurality of shares and distributed to different computing servers; a verifiable polynomial chain is constructed, a verification quantity and a mask are generated under additive secret sharing and returned to a client, and verification of the reasoning process is completed by designing a verification equation in a polynomial form. According to the method, reasoning verification is completed by designing a polynomial equation, and low-overhead and low-cost step-level verification with constant-level on-line verification calculation time of parallel calculation is realized while the integrity and privacy of whole-course calculation are ensured.

To provide a system and a method for converting high-level source code into an arithmetic circuit that represents the functions expressed in the source code.SOLUTION: A method for providing arithmetic enhancements of C-like smart contracts for verifiable computation includes processing a portion of high-level source code (e.g., a smart contract) to generate an arithmetic circuit C including one or more arithmetic gates that represent at least a portion of the functionality expressed in the source code. The processing evaluates one or more constants provided in the source code to produce one or more expressions including Boolean and / or arithmetic operators. The arithmetic circuit C includes n-bit wires connected to the arithmetic gates and is used to provide hardware and / or software circuits and to generate secondary programs executable on a processor.SELECTED DRAWING: Figure 1

Choosing blockchain validators includes providing a blockchain in which computing devices are participant devices that act on behalf of associated blockchain accounts that use the blockchain to transact a first type of assets and a second type of assets. Some computing devices are validating computing devices associated with validating blockchain accounts and run a prescribed validating computer program to take actions that include at least one of: validating blocks, validating transactions, or validating blockchain accounts in a given time period. A validating computing devices receives from a participant device a request for an associated blockchain account to become a validating blockchain account for a given period of time, causing the at least one validating computing device to use a cryptographically fair lottery to determine whether the associated blockchain account corresponding to the particular participant device is selected to become a validating blockchain account in the given period of time.

A system and method for establishing a verified computing environment for executing data-driven contracts, comprising a cryptographic directed acyclic graph object model of a data-driven contract, wherein at least a subset of the objects in the MDAG correspond to clause state of at least one programmable clause of the data-driven contract; at a computing environment, administrating the data-driven contract in accordance with the MDAG which can include at least one execution instance comprised of: receiving a contract input to contract logic of the data-driven contract, processing the input according to the clause logic, in response to the contract input, generating at least one updated state object and generating at least one output object, and for each generated object, hash-linking the generated object to an object associated with the creation of the generated object.

Aspects of the disclosure related to delta code identification and validation. A computing platform may use an AI engine to convert historical information into a machine readable format. The computing platform may configure a Q learning module. The computing platform may receive delta code and input the delta code into the Q learning module. The computing platform may output, using the Q learning module, one or more scenarios. The computing platform may output, using an association mapping module, one or more unit test cases. The computing platform may validate the delta code using the one or more unit test cases. The computing platform may send the validated delta code and commands directing an enterprise system to deploy the validated delta code.

In some aspects, a verification system can receive a verification query from a verifier computing system for requesting verification of characteristics of an entity involved in an online interaction. The verification query can include a unique identifier (“UID”) of the entity. The verification computing system can query a verification repository in the verification computing system based on the UID. Additionally, the verification computing system can query an external-source cache using the UID. In response to determine a match for the UID in the external-source cache, the verification computing system can request external sensitive data records for the entity from an external source corresponding to the external-source cache. Generating consolidated sensitive data records can involve consolidating the external sensitive data records and internal sensitive data records obtained through querying the verification repository. A verification result, generated using the consolidated sensitive data records, can be transmitted to the verifier computing system.

Various aspects of the disclosure relate to verification of data sets used for real-time processes and / or batch processes. A computing platform negotiates, by a first quantum node, a shared key group with at least a second quantum node and calculates an exclusive or (XOR) value of a pair of the first quantum node and the second quantum node. The first quantum service node performs a shared key grouping with the second quantum node and then selects a quantum key relay link between a real-time node and a batch source node. The computing platform selects a corresponding state of all virtual quantum nodes associated with the quantum key relay link and encapsulates a virtual quantum link state between any two quantum service nodes in the quantum network into a database decision engine data file.

Embodiments of the present application relate to the technical field of information security, and disclose a task proof method and device, a task execution method and equipment, and a storage medium. The task proof method comprises: dividing a to-be-executed computing task into multiple subtasks; selecting at least one sub-target task from the multiple subtasks based on a task selection rule; generating at least one arithmetic circuit, at least one proof key and at least one verification key corresponding to the at least one sub-target task based on the at least one sub-target task; sending the to-be-executed computing task, the at least one proof key and the at least one arithmetic circuit to a second server, receiving a computing result and a proof result of the second server; and proving the validity of the to-be-executed computing task based on the at least one verification key, the at least one arithmetic circuit, the proof result and the computing result. The task proof method disclosed in the present application solves the problem that a large amount of time is consumed in the generation of proof and verification processes, and makes the verification of a computing task more efficient.

The present invention relates to the field of machine learning privacy computing technology, and more specifically, to a method for secure outsourcing verification of floating-point matrix multiplication based on TEE and GPU. ′ ,Y ′ and Z ′ In this way, whether it is TEE or GPU, in the same calculation order, Z ′ Each element in must be consistent with X ′ Y ′ The product of the two elements is identical. Compared with existing solutions, this approach avoids verification errors caused by computer precision and the problem of GPUs producing erroneous results within a certain range due to tolerance that cannot be verified by the TEE. It also solves the problem of correctness verification for outsourced floating-point matrix multiplication.

The invention belongs to the field of formalized verification, and provides a MedTiny language formalized verification method based on theorem proof. According to the method, a target language similar to the MedTiny structure is designed in a theorem prover Isable, so that verification of the MedTiny program is realized; a theorem proving technology is used to enable a verification result to have strict mathematical guarantee; the Hall triad is simplified according to a preset Hall triad proving rule, so that the problem that the unbounded condition of the cycle index cannot be verified is avoided; according to the technical scheme of the invention, the simplified Hall triad is verified to verify whether the final value of the verification condition obtained through calculation is true or not and whether the weakest pre-condition is contained in the pre-conditions or not is judged, so that the high automation of the verification process is realized through the theorem prover, the manpower demand of experts is greatly reduced, and the verification efficiency and accuracy are remarkably improved.

A verification computing system obtains from a vendor computing device software product version information that identifies a most recent version of a software product available from a software vendor. It is determined that an updated version of the first software product is available that has not been tested by the verification computing system. The verification computing system causes a generation of a first test computing environment that comprises one or more computing hosts or virtual machines. The updated version of the first software product using the first test computing environment is tested. The verification computing system generates information that indicates that the updated version of the first software product failed or passed a test threshold.

Methods, systems, and computer-readable media for verification of configurations of compute clusters. An automatic computational process is used to statically and / or dynamically verify configurations of software components installed on one or more interconnected computing entities constituting a compute cluster. Cluster configuration data is obtained, including data representative of a configuration of the software components. The cluster configuration data is processed to identify errors relating to interactions between the software components. Errors may be reported to users and / or corrected by modifying the compute cluster configuration.

The invention discloses a deterministic computing architecture based on formalized proof and an operation method of the deterministic computing architecture, and belongs to the field of formalized verification, computer system structures, operating systems and security computing. And the trusted executor layer is constrained by the specification and runs on compatible hardware. The actuator comprises an optimal atomic execution path planner. According to the method, strict and verifiable isomorphic mapping is carried out on'formalized specifications' (a machine verifiable mathematical proof) which is used as a system basis and contains original first principle derivation and physical execution (hardware implementation) of the formalized specifications, a universal calculation execution environment is constructed, the environment can break through inherent contradictions in the prior art, and the method has the advantages of being high in calculation efficiency and high in practicability. Meanwhile, unprecedented efficiency, safety, certainty and autonomy are achieved, and an optimal calculation mode close to theory is achieved.

Examples disclosed herein include are computing device hardware components, computing devices, systems, machine-readable mediums, and interconnect protocols that provide for code object measurement of a peripheral device and a method for accessing the measurements to verify integrity across a computing interconnect (e.g., Peripheral Component Interconnect Express—PCIe). For example, a cryptographic processor of a PCIe endpoint (such as a peripheral) may take a measurement (e.g., computing a hash value) of a code object on the device prior to executing the code object. This measurement may be placed in a register that is accessible to another component, such as a host operating system across a PCIe bus for interrogation. The host operating system may utilize an interconnect protocol, such as a PCIe protocol to access the measurement. These measurements may be consumed by a Trusted Platform Manager or other components of a host system that may verify the measurements.

The invention provides systems and methods for converting high level source code into an arithmetic circuit which represents the functionality expressed in the source code. The invention comprises a translation / interpretation component for performing this conversion. In a preferred embodiment, the source code is a smart contract such as those used in relation to a blockchain platform. The invention could be used in relation to the Bitcoin network, for example. A method in accordance with an embodiment comprises the steps of: processing a portion of high level source code (e.g. a smart contract) to generate an arithmetic circuit. The arithmetic circuit comprises one or more arithmetic gates arranged to represent at least some of the functionality expressed in the source code. The processing involves evaluating one or more constants provided in the source code to produce one or more expressions that include Boolean and / or arithmetic operators.