Abstract: An example operation may include one or more of storing a public key and one or more corresponding addresses associated with a user profile in a blockchain, creating a credential for the user profile based on the public key, forwarding the credential to the one or more addresses, receiving a request for access to a site from a user device associated with the user profile, and retrieving the credential based on the one or more addresses from the blockchain.

Abstract: A virtual blockchain configuration may provide a distributed structure that uses a distributed hash configuration to reduce the complexity of blockchain transactions. One example method of operation may comprise one or more of storing a subset of blockchain data in a network device, accessing via the network device a virtual copy of a blockchain, accessing a blockchain block via the virtual copy of the blockchain, and writing blockchain transactions to the blockchain block via the network device.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include one or more of monitoring a computing service via various nodes operating on a blockchain, identifying a proposed change to the computing service, storing details of the proposed change in a smart contract, storing the smart contract as a transaction in the blockchain, and validating the proposed change of the smart contract.

Abstract: An example operation may include one or more of storing a public key and one or more corresponding addresses associated with a user profile in a blockchain, creating a credential for the user profile based on the public key, forwarding the credential to the one or more addresses, receiving a request for access to a site from a user device associated with the user profile, and retrieving the credential based on the one or more addresses from the blockchain.

Abstract: A method, computer system, and computer program product to detect anomalies in a multivariate or multidimensional time series data set. The time series data set is retrieved from a monitored device. A pair of neural networks are trained simultaneously using the retrieved time series data set by implementing an adversarial training process, to generate a generative neural network and a discriminative neural network. The anomalies in the time series data set of the monitored device are detected by implementing one or both of the generative neural network and the discriminative neural network to monitor the time series data set.

Abstract: Performing design optimization using an augmented reality system. Baseline data comprising baseline sensor data and baseline user input data is received by a computer system. An interactive baseline design optimization problem based on the baseline data is generated by the computer system. The baseline interactive optimization problem is transmitted by the computer system to the augmented reality system. Refined data comprising refined sensor data and refined user input data is received by the computer system. An interactive refined optimization problem based on the refined data and the baseline data is generated by the computer system. The interactive refined optimization problem is transmitted by the computer system to the augmented reality system.

Abstract: Performing design optimization using an augmented reality system. Baseline data comprising baseline sensor data and baseline user input data is received by a computer system. An interactive baseline design optimization problem based on the baseline data is generated by the computer system. The baseline interactive optimization problem is transmitted by the computer system to the augmented reality system. Refined data comprising refined sensor data and refined user input data is received by the computer system. An interactive refined optimization problem based on the refined data and the baseline data is generated by the computer system. The interactive refined optimization problem is transmitted by the computer system to the augmented reality system.

Abstract: An example operation may include one or more of storing a public key and one or more corresponding addresses associated with a user profile in a blockchain, creating a credential for the user profile based on the public key, forwarding the credential to the one or more addresses, receiving a request for access to a site from a user device associated with the user profile, and retrieving the credential based on the one or more addresses from the blockchain.

Abstract: An example operation may include one or more of identifying one or more data volume management policies from a plurality of different parties, storing the one or more data volume management policies in a smart contract stored on a blockchain, identifying one or more data access thresholds being exceeded on a network, modifying an operating status of the network based on the one or more policies and the one or more data access thresholds being exceeded, and storing the modified operating status in the blockchain.

Abstract: An example operation may include one or more of identifying a first conferred asset exchange request from a first user account and a second conferred asset exchange request from a second user account which are capable of being used to settle each other, requesting an intermediary blockchain to perform a conferred asset settlement transaction for the first and second conferred asset exchange requests, determining that first conferred assets of the first user account and second conferred assets of the second user account have been transferred to temporary intermediary trading addresses, respectively, and releasing the first conferred assets to the second user account and the second loyalty assets to the first user account, in response to the determining.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include one or more of monitoring a computing service via various nodes operating on a blockchain, identifying a proposed change to the computing service, storing details of the proposed change in a smart contract, storing the smart contract as a transaction in the blockchain, and validating the proposed change of the smart contract.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include one or more of storing original data in a blockchain, storing transformed data based on the original data in the blockchain, storing chaincode on the blockchain used to transform the original data to the transformed data, and retrieving a transaction from the blockchain with the transformed data and the chaincode.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification. One example operation may comprise one or more of identifying an updated software build, creating a hash based on the updated software build, storing the hash of the updated software build in a blockchain, and storing a binary representation of the updated software build in a distributed hash table (DHT).

Abstract: A virtual blockchain configuration may provide a distributed structure that uses a distributed hash configuration to reduce the complexity of blockchain transactions. One example method of operation may comprise one or more of storing a subset of blockchain data in a network device, accessing via the network device a virtual copy of a blockchain, accessing a blockchain block via the virtual copy of the blockchain, and writing blockchain transactions to the blockchain block via the network device.

Abstract: A key value storage (KVS) system comprising: a client-side agent configured to encrypt data; three nodes hosted respectively in three cloud service providers, wherein each node comprises: a management node configured to receive encrypted data from the client-side agent, a homomorphic encryption (HE) key manager configured to fetch a public key of a given object in the KVS system, a homomorphic encryption and processing engine configured to execute commands over the encrypted data without decrypting it, a homomorphic memory store, a hypervisor configured to monitor performance of the management node in order to assess the quality of service of the management node; and wherein each node serves on a rotating basis in a master node role, a secondary node role, or a back-up node role, wherein the nodes rotate their roles when the master node's hypervisor detects a reduced quality of service of the master node's management node.

Abstract: An apparatus comprising: a virtual machine (VM) base image database; a VM image generator configured to build in the VM base image database a corpus of possible VMs that may run on a cloud service provider; an energy profiler configured to generate energy profiles offline of each permutation in the VM base image database under several different operating conditions; an energy profile database populated with the energy profiles generated by the energy profiler; and a monitor configured to monitor energy patterns in side-channels at the VM level and to compare the energy patterns for each VM operating on the cloud service provider with the energy profiles stored in the energy profile database, and further configured to trigger a self-cleansing cycle when a given real-time energy pattern deviates from its corresponding energy profile by a predetermined threshold amount.

Abstract: An apparatus comprising: a virtual machine (VM) base image database; a VM image generator configured to build in the VM base image database a corpus of possible VMs that may run on a cloud service provider; an energy profiler configured to generate energy profiles offline of each permutation in the VM base image database under several different operating conditions; an energy profile database populated with the energy profiles generated by the energy profiler; and a monitor configured to monitor energy patterns in side-channels at the VM level and to compare the energy patterns for each VM operating on the cloud service provider with the energy profiles stored in the energy profile database, and further configured to trigger a self-cleansing cycle when a given real-time energy pattern deviates from its corresponding energy profile by a predetermined threshold amount.

Abstract: A key value storage (KVS) system comprising: a client-side agent configured to encrypt data; three nodes hosted respectively in three cloud service providers, wherein each node comprises: a management node configured to receive encrypted data from the client-side agent, a homomorphic encryption (HE) key manager configured to fetch a public key of a given object in the KVS system, a homomorphic encryption and processing engine configured to execute commands over the encrypted data without decrypting it, a homomorphic memory store, a hypervisor configured to monitor performance of the management node in order to assess the quality of service of the management node; and wherein each node serves on a rotating basis in a master node role, a secondary node role, or a back-up node role, wherein the nodes rotate their roles when the master node's hypervisor detects a reduced quality of service of the master node's management node.

Abstract: Embodiments of the invention relate to evaluation and storage of data in a computer system configured with a shared pool of resources. A multi-level adaptive compression technique is employed to minimize the cost of data storage based upon the type of data being stored and their access pattern. The costs of data storage include capacity, bandwidth, and compute cycles. Data is transformed local to a client in communication with the shared pool, local to the shared pool, or as a combination with a partial transformation local to the client and a partial transformation local to the shared pool.

Abstract: Embodiments of the invention relate to evaluation and storage of data in a computer system configured with a shared pool of resources. A multi-level adaptive compression technique is employed to minimize the cost of data storage based upon the type of data being stored and their access pattern. The costs of data storage include capacity, bandwidth, and compute cycles. Data is transformed local to a client in communication with the shared pool, local to the shared pool, or as a combination with a partial transformation local to the client and a partial transformation local to the shared pool.