45 results about "Verified computing" patented technology

Disclosed are systems and methods for a hybrid cloud-edge computing platform using decentralized networks for solving resource-intensive computation tasks such as machine learning and video processing tasks. In some respects, the cloud-edge computing platform comprises a coordinator cluster and worker nodes partitioned into shards, which include cloud-based networks and edge networks, and which cater to a wide range of computation requirements. The coordinator cluster manages workloads by selecting the appropriate shard and worker nodes to execute tasks based on computed efficiency scores. Worker nodes may be incentivized with rewards such as cryptocurrency tokens for successful completion of tasks. The disclosed architecture also supports the pipelining of multiple tasks in a workload, where the output of one task is used as input for another task. In some respects, the computing architecture includes a blockchain-supported edge network, which enables verifying compute tasks and managing reward distribution for worker nodes using smart contracts.

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 discloses an abnormal operator positioning method and device, a storage medium and a program product, and relates to the technical field of computers, and the method comprises the steps: rapidly locking the candidate range of an abnormal operator through comparing the operation result difference of a target model in different computing devices, and avoiding the resource waste of total operator troubleshooting; dynamically generating a to-be-verified operator set according to the operators called by the target model, and compressing the troubleshooting range from the whole operator set to a set corresponding to the operators called by the target model; the technical problem of low efficiency in a manual layer-by-layer verification method is solved by returning to verification computing equipment one by one and combining automatic result comparison and accurate positioning of abnormal operators, and the technical effects of improving the troubleshooting efficiency and avoiding the risk of manual misoperation are achieved.

A method for verifying an application structured to execute on a client device. A challenge request is sent to the application. A candidate challenge answer is received from the application in response to the challenge request, which is then provided as input to a verification computation with a challenge input. Based on an output of the verification computation, it is determined that the candidate challenge answer is generated by providing the challenge input to a challenge computation. Based on the determination that the candidate challenge answer is generated by providing the challenge input to the challenge computation, the application is verified.

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.

The invention provides a block chain verification service management method and system, a block chain comprises a plurality of block chain nodes, the block chain verification service management system comprises a plurality of shared nodes and a plurality of special nodes, and the shared nodes and the special nodes are used as the block chain nodes; and the shared node stores synchronous data of the block chain. The method comprises the following steps: receiving a user node creation request from a first user, creating at least one special node according to data of a first shared node in a plurality of shared nodes, and using the at least one special node as the user node of the first user; receiving first data from a first user verifying the computing application; second data are generated according to the first data, and the second data comprise the first data, the identifier of the first user and the identifier of the user node; and sending the second data to the plurality of block chain nodes. According to the method and the system, the effectiveness of the user node in the block chain can be remarkably improved.

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.

An attestation service is configured to receive a request to enable attestation for a compute instance according to an attestation policy indicating one or more baseline health measurement values for validating compute instances. The attestation service provides a network endpoint for the compute instance to request attestation. The attestation service receives, via the network endpoint from a compute instance, one or more health measurement values of the compute instance. The attestation service validates the compute instance based at least on a comparison of the one or more current health measurement values and the one or more baseline health measurement values. The attestation service, in response to validating the compute instance, generates an attestation token indicating that the compute instance is authorized to access a secured resource of the provider network.

A method for verifying an application structured to execute on a client device. A challenge request is sent to the application. A candidate challenge answer is received from the application in response to the challenge request, which is then provided as input to a verification computation with a challenge input. Based on an output of the verification computation, it is determined that the candidate challenge answer is generated by providing the challenge input to a challenge computation. Based on the determination that the candidate challenge answer is generated by providing the challenge input to the challenge computation, the application is verified.

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.

An embodiment of the present application provides a verification method, apparatus, computer, and computer configuration system. The verification method includes: in response to a computer power-on boot instruction, a processor reads BIOS code and BIOS verification information from a BIOS chip of the computer, where the BIOS code stores a unique identifier of computer hardware of the computer; the processor performs BIOS code security verification based on the BIOS code and the BIOS verification information; if the BIOS code security verification passes, the processor runs the BIOS code to start the work of computer power-on initialization, and the work includes verifying computer hardware; during the process of verifying computer hardware, according to the unique identifier of the computer hardware pre-stored in the BIOS code, it is verified whether the computer hardware of the computer is legal. The embodiment of the present application can, at the computer power-on boot stage, through the two-way verification of BIOS code security verification and computer hardware legality verification, ensure the reliability of computer verification, thereby improving the security of the computer.

A method and a system for dynamically deriving and verifying a measure of a computing environment is presented. The proposed method and system are used to reliably verify measurements of the computing environment. The method includes receiving a dataset recorded by an untrusted source describing elements used to create a computing system operating in a computing environment, receiving attestation evidence generated by a trusted source including an initial measurement value describing the elements of the computing system, deriving a measurement value based on the received dataset, and performing a verification process on a measurement of the computing environment. The verification process is performed by comparing the derived measurement value with the measurement value of the attestation evidence. In response to the comparison of the derived measurement value with the measure value of the attestation evidence being equal, trustworthiness of the computing environment is determined.

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.

The present application discloses a method, device, storage medium and program product for locating abnormal operators, relating to the field of computer technology. It includes quickly locking the candidate range of abnormal operators by comparing the operation result differences of the target model on different computing devices, avoiding the waste of resources in checking all operators; dynamically generating a set of operators to be verified according to the operators called by the target model, and compressing the checking range from the entire operator set to the set corresponding to the operators called by the target model; accurately locating the abnormal operators by gradually reverting to the verification computing device one by one and combining with automated result comparison, solving the technical problem of low efficiency existing in the manual layer-by-layer verification method, and achieving the technical effects of improving the checking efficiency and avoiding the risk of manual operation errors.