Abstract: Methods and systems are presented for providing a framework for facilitating multi-party computation within a sharding environment. After a blockchain is divided into multiple shard chains, a multi-party computation system obtains attributes associated with a first shard chain. The attributes may represent characteristics of the first shard chain, characteristics of transactions recorded in the first shard chain, and characteristics of the computer nodes configured to manage the first shard chain. Based on the attributes, the multi-party computation system determines a multi-party computation scheme that specifies a minimum threshold number of nodes required to participate in a transaction validation process and at least one required node required to participate in the transaction validation process for the first shard chain.

Abstract: Methods and systems are presented for providing a multi-party computation (MPC) framework for dynamically configuring, deploying, and utilizing an MPC system for performing distributed computations. Based on device attributes and network attributes associated with computer nodes that are available to be part of the MPC system, a configuration for the MPC system is determined. The configuration may specify a total number of computer nodes within the MPC system, a minimum number of computer nodes required to participate in performing a computation process, a key distribution mechanism, and a computation processing mechanism. Encryption keys are generated and distributed among the computer nodes based on the key distribution mechanism. Upon receiving a request for performing the computation, updated network attributes are obtained.

Abstract: Methods and systems are presented for providing a framework for facilitating multi-party computation within a sharding environment. After a blockchain is divided into multiple shard chains, a multi-party computation system obtains attributes associated with a first shard chain. The attributes may represent characteristics of the first shard chain, characteristics of transactions recorded in the first shard chain, and characteristics of the computer nodes configured to manage the first shard chain. Based on the attributes, the multi-party computation system determines a multi-party computation scheme that specifies a minimum threshold number of nodes required to participate in a transaction validation process and at least one required node required to participate in the transaction validation process for the first shard chain.

Abstract: Quantum computers with a limited number of input qubits are used to perform machine learning processes having a far greater number of trainable features. A list of features of a field are divided into a plurality of feature groups. Each of the feature groups includes a respective group of some, but not all, of the features. A first machine learning process is performed to train a first instance of a quantum computer model, where the feature groups are used as inputs. Based on the first machine learning process being performed, a subset of the feature groups is selected for a second machine learning process. Thereafter, the second machine learning process is performed to train one or more second instances of the quantum computer model. The individual features of the selected subset of the feature groups are used as inputs for the second instances of the quantum computer model.

Abstract: Methods and systems are presented for providing a framework for facilitating multi-party computation within a sharding environment. After a blockchain is divided into multiple shard chains, a multi-party computation system obtains attributes associated with a first shard chain. The attributes may represent characteristics of the first shard chain, characteristics of transactions recorded in the first shard chain, and characteristics of the computer nodes configured to manage the first shard chain. Based on the attributes, the multi-party computation system determines a multi-party computation scheme that specifies a minimum threshold number of nodes required to participate in a transaction validation process and at least one required node required to participate in the transaction validation process for the first shard chain.

Abstract: Methods and systems are presented for providing a multi-party computation (MPC) framework for dynamically configuring, deploying, and utilizing an MPC system for performing distributed computations. Based on device attributes and network attributes associated with computer nodes that are available to be part of the MPC system, a configuration for the MPC system is determined. The configuration may specify a total number of computer nodes within the MPC system, a minimum number of computer nodes required to participate in performing a computation process, a key distribution mechanism, and a computation processing mechanism. Encryption keys are generated and distributed among the computer nodes based on the key distribution mechanism. Upon receiving a request for performing the computation, updated network attributes are obtained.

Abstract: Methods and systems are presented for providing a secured framework for facilitating electronic transactions using a multi-party computation approach. Under the multi-party computation approach, the task of authenticating a transaction conducted through a user account is distributed among multiple computer nodes. One or more secrets and shares of a secret are distributed among the multiple computer nodes. An authentication process is implemented such that at least a portion of the multiple computer nodes, including one or more required nodes, exceeding a predetermined number of nodes are needed to perform a set of computations using the corresponding secret(s) and/or shares of the secret in order to generate a digital signature for the user account. By verifying the digital signature using a public key of the user account, it can be determined that the participation requirement has been satisfied.

Abstract: A cache management system, method, and computer-readable medium which manage caching of resources are provided. The method includes receiving a request for a resource including a hierarchical resource locator, fetching the resource from a node upon determining that the resource is not stored in a cache, adding an entry for the resource to a mapping table associated with the cache, the entry including the resource locator and dependency information for dependent resources identified from the hierarchical structure of the resource locator, and updating entries in the mapping table for master resources identified from the hierarchical structure of the resource locator, the updated entries including an identifier for the resource.

Abstract: A cache management system, method, and computer-readable medium which manage caching of resources are provided. The method includes receiving a request for a resource including a hierarchical resource locator, fetching the resource from a node upon determining that the resource is not stored in a cache, adding an entry for the resource to a mapping table associated with the cache, the entry including the resource locator and dependency information for dependent resources identified from the hierarchical structure of the resource locator, and updating entries in the mapping table for master resources identified from the hierarchical structure of the resource locator, the updated entries including an identifier for the resource.

Abstract: A cache management apparatus, method, and computer readable medium which manages caching of resources. The method includes analyzing a structure of a resource in a system which exposes resources to clients, generating a dependency graph of objects linked to a resource based on the analyzed structure of the resource, and managing caching of resources based on the generated dependency graphs. A generated dependency graph includes hierarchical dependency information with respect to the objects of the resource.

Abstract: A cache management apparatus, method, and computer readable medium which manages caching of resources. The method includes analyzing a structure of a resource in a system which exposes resources to clients, generating a dependency graph of objects linked to a resource based on the analyzed structure of the resource, and managing caching of resources based on the generated dependency graphs. A generated dependency graph includes hierarchical dependency information with respect to the objects of the resource.