Abstract: An example data storage device includes a memory and a controller. The controller is configured to store at least one of the one or more data elements utilizing differential compression. The controller is further configured to receive a data element to be stored, generate a copy of the data element to be stored, and mask data to be anonymized by deleting one or more portions to be anonymized. The controller is further configured to generate similarity hashes for one or more portions of the copy of the data element with masked data for finding one or more reference portions, and compress the data element to be stored utilizing differential compression with reference to the one or more reference portions.

Abstract: Method prevents duplicate data to be stored in storage having hosts which do not trust each other. The method includes storage including encrypted data blocks, network further including distributed ledger, accessible to each of two or more hosts. The method includes steps, performed by first host when the first host wishes to store a new data block, obtaining first hash value for new data block, determining if first hash value is found in ledger. If first hash value is not found in ledger, creating set of confirmation data, encrypting new data block with block-unique encryption key, and storing first ownership record in ledger. If first hash value is found in ledger, obtaining information about second host that has already stored previous block identical to new data block, entering in ledger key request, receiving from ledger key transfer record, sending to ledger new ownership record.

Abstract: A replication system for data of mobile devices is disclosed. The data of a mobile device is uploaded to stations in an area. Metadata associated with the objects is stored in a centralized or decentralized system. The metadata can be accessed to identify the stations storing the device's objects and the data of the mobile device can then be retrieved from the stations and reconstructed.

Abstract: A computer-implemented data backup method comprises storing metadata associated with an object in a secondary storage layer of a backup system, the metadata representing a data structure for the object, dividing a set of data representing the object into multiple variable length chunks, determining whether an existing chunk of data that is the same as at least a part of the variable length chunk exists in a primary storage layer of the backup system, storing the variable length chunk in the primary storage layer of the backup system, and on the basis of the determination, providing the primary storage layer of the backup system with an indication of the location of the existing chunk of data.

Abstract: One example method includes chunking a respective disk of each of a plurality of virtual machines (VM) to create a respective plurality of chunks associated with each of the VMs, creating, based on the chunking process, a cluster comprising one or more of the VMs, creating a VM template whose data and disk structure match respective data and disk structures of each of the VMs in the cluster, and in response to a file operation involving a first one of the VM disks, defragmenting the first VM disk so that a disk structure of the first VM disk is the same as a disk structure of the VM template.

Abstract: A data storage arrangement includes a memory and a controller, where the controller receives an indication of data to be anonymized. The controller further parses a data element to be stored and generates a copy of one or more data portions to be anonymized. The controller further deletes one or more data portions to be anonymized to generate a modified data element to be stored. The controller further generates a copy of the modified data element to be stored utilizing deduplication. The data storage arrangement thus takes in account data anonymization during deduplication (i.e. an anonymization aware deduplication).

Abstract: One example method includes creating an empty reconstruction stream database, identifying a data time interval, identifying data sources in which data was stored during the data time interval, reading data from the data sources, where the data read out from the data sources are associated with respective timestamps that fall within the data time interval, inserting the read out data into the empty reconstruction stream database so as to create a high resolution data stream, where the data are ordered in the empty reconstruction stream database according to timestamp, processing the data in the high resolution data stream and, based on the processing of the data, identifying and resolving a problem relating to an operating environment in which the data was initially generated.

Abstract: Deduplication of files or other data or objects in a manner that is aware of a format of the file and the application. A file may be chunked based on the format. The chunks are more consistent and lead to higher deduplication ratios. The file may be presented as a single file. However, the file is stored in chunks or subfiles and deduplication is performed with respect to the chunks. When the file is read, the file is rebuilt from its respective chunks. The files may also be compressed using differential compression, which leverages the content of similar files to compress a current file.

Abstract: One example method includes creating a backup of data, creating metadata associated with the backup, hashing the backup to create a backup hash, obtaining a key from a blockchain, generating an aggregate hash of a combination that includes the key and the backup hash, and transmitting the aggregate hash to a blockchain network. Because the aggregate hash is not modifiable when stored in a blockchain, an immutable record exists that establishes when a particular backup was created.

Abstract: A block storage device, for data compression is configured to, in a first operating phase, if it is determined, by the block storage device, that a data block is to be written to a large block storage area of the block storage device, determine if the data block can be de-duplicated. If the data block cannot be de-duplicated, the block storage device stores the data block using large block compression.

Abstract: A device for merging backup policies is configured to determine, if a first backup policy comprising a first set of rules, and a second backup policy comprising a second set of rules, are assigned to a backup object. The device is further configured to, when the first backup policy and the second backup policy are assigned to the backup object, generate a merged backup policy comprising a merged set of rules, based on the first backup policy and the second backup policy. A resource consumption of a backup created according to the merged backup policy is below a predefined threshold.

Abstract: A data manager includes persistent storage and a data register. The persistent storage stores an identity chain and a data availability chain. The data register obtains data associated with an entity registered with the identity chain using a public key associated with the entity; obtains an object identifier associated with the data by storing the data in a data storage as a record; and records, on the data availability chain, both of: the record using a private key associated with the entity, and the object identifier.

Abstract: A data protection system configured to backup a time series database is provided. The data protection system may be integrated with or have access to consolidation policies of the time series database. The backup policy and backup retention policy are set by monitoring the consolidation policy and adjusting the backup policy to ensure that the data in the time series database is protected prior to being downscaled, discarded or otherwise consolidated.

Abstract: Managing backup copies in a right to delete personal data environment is described. A system creates a revised backup copy by deleting any data that a deletion request ledger specifies for deletion from a backup copy that was created for a data object. The system associates an updating time with the revised backup copy. The system retrieves the revised backup copy in response to receiving a restoration request corresponding to the revised backup copy. The system enables restoration of the data object by deleting any data i) that the deletion request ledger specifies for deletion from the revised backup copy and ii) that is associated with a deletion request time which is subsequent to the updating time.

Abstract: A method for backing up data item stored in host device, includes activating backup agent in host file system of host device, the host file system including data item to be backed up. The method includes using the activated backup agent for detecting one or more first operations executing one or more changes in the host file system, for detecting the one or more first changes in the host file system executed by the one or more first operations, and for generating a first data backup instruction based on the detected one or more first operations and on the detected one or more first changes. The method further includes providing one or more operation algorithms to a backup system; and providing the generated first data backup instruction to the backup system configured for delayed backup computation of the one or more data items to be backed up.

Abstract: In a multi-cloud computing environment comprising a plurality of cloud platforms with each cloud platform comprising one or more nodes, a method maintains a decentralized metadata database framework, wherein each node comprises a decentralized metadata database component operatively coupled to each other decentralized metadata database component of the framework and wherein each of at least two of the decentralized metadata database components stores a set of metadata records corresponding to protected data stored across the plurality of cloud platforms. Further, the method manages one or more access requests directed to the protected data through one or more of the decentralized metadata database components of the framework.

Abstract: One example method includes discovering an application topology, discovering relationships between microservices that are elements of the application topology, ranking the microservices, identifying one or more of the microservices as a persistency microservice, selecting one or more persistency microservices for backup, and defining a backup policy based on the microservice relationships, the microservice rankings, and the selected persistent microservices. A backup operation is then performed that includes backing up persistent data and/or persistent metadata generated and/or modified by one or more of the persistency microservices.

Abstract: One example method includes receiving an IO request that specifies an operation to be performed concerning a data block, determining if a policy exists for a device that made the IO request, when a policy is determined to exist for the device, comparing the IO request to the policy, recording the IO request, and passing the IO request to a disk driver regardless of whether the IO request is determined to violate the policy or not.

Abstract: One example method includes performing a machine learning process that involves performing an assessment of a state of a computing system, and the assessment includes analyzing information generated by an IoT edge sensor in response to a sensed physical condition in the computing system, and identifying an entity in the computing system potentially impacted by an event associated with the physical condition.

Abstract: A system and method for differential compression are disclosed. In the disclosure, input data blocks selected for compression are received. For each input data block: the input data block is divided into at least two segments. For each of the at least two segments, a similarity degree between the respective segment and each of the data blocks excluding the respective data block is computed. For each of the at least two segments, the data block which has a biggest similarity degree with the respective segment among the data blocks excluding the respective data block is selected as an optimal reference data block for the respective segment. The differential compression is applied to the input data block and optimal reference blocks in response to determine a differential compression is to be applied based on the similarity degree between the segments of the input data block and the corresponding optimal reference blocks.