One example method, which may be performed in connection with an object store, includes receiving a key of a key-value pair, correlating the key to a location in a base of a Merkle tree, inserting the key at the location, hashing the value associated with the key to produce a data hash, and inserting the data hash in the Merkle tree. The Merkle tree may then be checked for consistency, and synchronized with another Merkle tree. The Merkle tree may be of a fixed size, and insertion of the key in the Merkle tree does not change the location of any keys existing in the Merkle tree prior to insertion of the new key.

A building system for operating a building and managing private building information includes a processing circuit configured to receive a request for information for a building entity of a building entity database. The processing circuit is configured to select one of the mask templates from the entity database based on access values associated with the requesting device and a relational link between the building entity and the mask templates, retrieve private information for the building entity in response to a reception of the request for the information, and generate a masked information data structure based on the private information and the one of the mask templates.

A method performs efficient data searches in a distributed computing system. The method may include, receiving a first key. The method may further include determining a hash map associated with the first key from among a plurality of hash maps. In some examples, the obtained hash map maps a partition of a set of keys to particular index values. The method may further include determining an index value associated with a second key using the determined hash map. The method may further include determining transaction processing data associated with the first key using the determined index value and providing the transaction processing data. Utilization of the plurality of hash maps may enable a data search to be performed using on-board memory of an electronic device of the distributed computing system.

The invention provides a secure method for exchanging entities via a blockchain. The invention incorporates tokenisation techniques, and also techniques for embedding metadata in a redeem script of a blockchain transaction. Embodiment(s) provide a method of: generating a first script, the first script comprising: a first set of metadata associated with a first invitation for the exchange of a first entity by a first user, the first set of metadata comprising an indication of the first entity to be offered for exchange and a first location condition for the exchange, a first user public key (P1A) associated with the first user, wherein the first user public key (P1A) is part of an asymmetric cryptographic pair comprising the first user public key (P1A) and a first user private key (V1A). The script may further comprise and a first third-party public key (P1T) associated with a first third-party, wherein the first third-party public key (P1T) is part of an asymmetric cryptographic pair comprising the first third-party public key (P1T) and a first third-party private key (V1T) The method further comprises the steps of hashing the first script to generate a first script hash and publishing the first script and the first script hash on a distributed hash table (DHT).

Systems and methods are disclosed herein for reducing storage space used in tracking behavior of a plurality of network endpoints by modeling the behavior with a behavior model. To this end, control circuitry may determine a respective network endpoint, of a plurality of network endpoints, to which each respective record of a plurality of received records corresponds. The control circuitry then may assign a dedicated queue for each respective network endpoint, and transmit, to each dedicated queue, each record that corresponds to the respective network endpoint to which the respective dedicated queue is assigned. The control circuitry may then determine, for each respective network endpoint, a respective behavior model, and may store each respective behavior model to memory.

A database system uses byte ordering for keys and a trie index to reference stored data. The keys of a database are converted into byte-comparable sequences of byte values. The trie index is generated including nodes connected by edges defining paths from a root node to leaf nodes. Each edge is associated with at least one byte value such that each path from the root node to a leaf node through one or more edges defines a unique byte prefix for a byte-comparable sequence of byte values. The leaf node of each path is associated with a database location value. A record is accessed in the database using a database location value determined from referencing the trie index using a byte-comparable sequence of byte values of the record generated from a key of the record. A trie structure and byte ordered keys may be used for partition or row indices.

A method for publishing a smart contract includes: generating a version number index value according to a contract name of the smart contract, and searching for an associated target contract version number from a blockchain network according to the version number index value; generating a contract index value according to a contract version number of the smart contract and the contract name, in response to determining that the contract version number of the smart contract is greater than the target contract version number; associating the contract index value with the smart contract and associating the version number index value with the contract version number of the smart contract, to generate transaction information; and publishing the transaction information to the blockchain network, to publish the smart contract to the blockchain network.

Systems, devices, and methods discussed herein are directed to modifying aspects of a compute instance. A user may request a change to the compute instance. The system may derive a state object indicating a future state of the compute instance were the change to be applied. A hash of a subset of the state object's attributes may be computed and provided to the requesting computing component. The system may subsequently proceed with applying the change. A current state object indicating a current state of the compute instance may be derived based on applying the change. An additional hash of the subset of the current state object's attributes may be computed and provided to the requesting computing component. The two hashes may be configured to enable the requesting computing component to verify the change to the compute instance has been implemented.

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.

A data processing system may store a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read a the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.