Abstract: A method, apparatus, and system for compressing a data object for storage at an object store of a cloud computing platform using a global compression scheme is disclosed. The operations comprise: receiving a new data object for storage in an object store on a cloud computing platform; dividing the new data object into a plurality of chunks of a predetermined size; for each chunk of the new data object, determining a respective most similar existing chunk already stored in the object store; compressing the new data object, comprising compressing each chunk of the new data object based on the respective most similar existing chunk as a compression reference; and storing the compressed new data object in the object store.

Abstract: Described is a system for securing recovery information that is distributed amongst multiple cloud-based systems. Encrypted recovery data may be stored on at least one cloud-based system. To decrypt the recovery data, coordination between multiple cloud-based systems may be required to obtain the encryption key. Accordingly, a production system does not have to perform key management. Therefore, even if the production system is compromised by a malicious party, the encryption key remains secure as multiple cloud-based systems would also have to be comprised. In addition, the system may coordinate the creation and distribution of the recovery information, as well as the acquisition of such recovery information as part of a data recovery process. Thus, the system may secure recovery information by leveraging multiple cloud-based systems (or services).

Abstract: Described is a system for intelligently storing and recovering backup data using multiple storage tiers of a cloud-based storage. The intelligent storing of backup data may leverage different cost structures associated with various cloud-based storage tiers by efficiently distributing data to more cost effective tiers. The system may also provide a coordinated (e.g. phased) recovery that prioritizes the recovery of certain files so that a user can gain access to such files in a shorter amount of time. The system may also provide enhanced storage and recovery functionality (e.g. via specialized user interface elements) by leveraging placeholder files to offload and recover individual files, and expedite the recovery of individual files during a substantial recovery process.

Abstract: Described is a system for distributing data amongst storage components using data sensitivity (or security) classifications. The system may define categories for classifying data files and assign a sensitivity (or security) rating to each of the defined categories. The categories and/or associated sensitivity ratings may be determined using machine learning components that may leverage industry-specific information or data sensitivity information used by other clients. The system may then continuously reevaluate (or reclassify) data files to determine whether they are stored on a storage component that meets the necessary data sensitivity requirements. If the system determines particular data files are stored on a corresponding storage component that does not meet certain data sensitivity requirements, the system may perform an action to secure the particular data files.

Abstract: Data protection operations including replication operations, transport operations, and/or access operations. A data protection engine may include a function as a service that allows data to be replicated and transported intracloud and intercloud. The data protection engine also allows point-in-time access to data stored in the cloud and/or replicated in the cloud.

Abstract: One example method includes receiving multiple raw data streams, each of the raw data streams including data generated and/or collected by a respective IoT device, storing the data of the raw data streams, splitting the data of the raw data streams into ‘N’ storage data streams, and transmitting each of the storage data streams to a different respective storage node. In this example, one of the storage nodes is a production edge node that retains one of the storage data streams, and each of N?1 other storage nodes receives a respective one of the storage data streams.

Abstract: One example method includes accessing stored data, associating a unique identifier with the data, creating a hash by hashing a combination that comprises the unique identifier and the data, transmitting the hash to a notary service, receiving, from the notary service, a digital signature that corresponds to the hash, appending the digital signature to the data, and storing, as an object, a combination that comprises the digital signature, the data, and the unique identifier.

Abstract: In a public cloud that stores data in a database system for a plurality of entities as primary data and as one or more secondary backup copies of the primary data, the data being stored in predefined data fields of data records, personal private data of each entity is stored encrypted using an encryption/decryption key that is unique to each different entity. The encryption/decryption keys are stored in the cloud in a key store of a key management system. To delete the personal private data of a particular entity, as to comply with the right to be forgotten pursuant to GDPR regulations, or otherwise, the encryption/decryption key for that particular entity is deleted from the key store to render permanently inaccessible all copies of that entity's personal private data.

Abstract: A method, apparatus, and system for compressing a data object for storage at an object store of a cloud computing platform using a global compression scheme is disclosed. The operations comprise: receiving a new data object for storage in an object store on a cloud computing platform; dividing the new data object into a plurality of chunks of a predetermined size; for each chunk of the new data object, determining a respective most similar existing chunk already stored in the object store; compressing the new data object, comprising compressing each chunk of the new data object based on the respective most similar existing chunk as a compression reference; and storing the compressed new data object in the object store.

Abstract: In a system that replicates data writes by a server to form a local copy for a local production site with local storage and a remote copy for a remote recovery site having remote storage, ransomware is detected by a decrease of more than a predetermined threshold in either or both of compression ratio or deduplication ratio in a length of data selected by a sliding time window. Upon detecting ransomware, data writes to said remote storage are stopped to minimize corruption of the remote data.

Abstract: Systems and methods for replicating a device image to a storage such as the cloud. The cloud is seeded with a base image that corresponds to the device. Changes between the contents of the device and the base image are identified, uploaded to the cloud, and applied to the image. The changes are tracked continuously and the image in the cloud can thus be used to restore the device to any point in time. The cloud image can also be used in a cloud based virtual machine that provides a user of the device with access to the device's contents via the cloud based image.

Abstract: The management and backup of image and video media is automatically performed by evaluating a media file to characterize the content; transforming the media file, as by compressing it, based upon its evaluation and established policies and requirements; and storing the transformed media file with a high resolution in a storage tier having first access characteristics for a first retention period. Following the first retention period, the stored file is re-evaluated and further transformed and stored with lesser resolution in another tier having different access characteristics for a second retention period. Subsequently, the further transformed media file may be transformed again and stored in archive storage.

Abstract: Embodiments are described for determining a customer value of a deduplication service. Customer data deduplication ratios are measured over a predetermined period of time in response to one or more events for a storage device. For each event, a deduplication ratio of customer data is stored in association with the storage device, customer ID, and configuration of the storage device. An event is an expiration of the predetermined period of time, or receiving notice of a configuration change of how the storage device is utilized by a customer. A configuration change can be adding or removing a virtual desktop, or adding or deleting one or more types of application data to/from the storage device. The storage deduplication statistics, configuration information are processed and sent to a storage service, with a storage device ID, and customer ID. A customer receives an analysis and statement of account from the storage service.

Abstract: A method, apparatus, and system for storing data at a multi cloud-based storage system is disclosed. The operations comprise: receiving a data block at a first cloud of a multi cloud-based storage system for storage, the multi cloud-based storage system comprising a first number (n) of clouds; generating the first number (n) of coded blocks at the first cloud based on the data block, wherein the data block is recoverable from any second number (k) out of the first number (n) of coded blocks, and wherein the second number (k) is greater than 1 and less than the first number (n); and distributing, by the first cloud, the first number (n) of coded blocks to the first number (n) of clouds of the multi cloud-based storage system, each of the clouds including the first cloud receiving a respective one of the first number (n) of coded blocks for storage.

Abstract: One example method includes implementing a function as a service (FaaS) at a datacenter by performing operations including receiving an application program interface (API) gateway call from a client application, wherein the API gateway call is associated with an object PUT request, and automatically triggering, with the API gateway call, performance of an object insertion function. The object insertion function includes retrieving, from backend object storage, a previous version of the object, differentially compressing the object relative to the previous version of the object so as to generate a differential, and storing the differential in the backend object storage.

Abstract: One example method includes receiving user input concerning a data protection policy for an entity, where the user input is in the form of written input and/or audio input, when the user input comprises audio input, translating the audio input into text, determining an intention of the user with respect to data protection for the entity by translating the text to common terms by interpreting terms of the text that have the same meaning as being similar words and applying context to the words, identifying a data protection policy that best corresponds to the intention of the user concerning data protection for the entity, and applying the data protection policy to the entity.

Abstract: In a system that replicates data writes by a server to form a local copy for a local production site with local storage and a remote copy for a remote recovery site having remote storage, ransomware is detected by a decrease of more than a predetermined threshold in either or both of compression ratio or deduplication ratio in a length of data selected by a sliding time window. Upon detecting ransomware, data writes to said remote storage are stopped to minimize corruption of the remote data.

Abstract: Disclosed is a method, apparatus, and system for collecting video data relating to a security event at a security operations center (SOC), the operations comprising: receiving video data captured through one or more cameras installed at one or more vehicles within a predetermined range of the security event at the SOC from the one or more vehicles; and compiling the video data into viewable format usable in an investigation of the security event.

Abstract: Embodiments of a compliance service that will enable users be compliant with all regulatory, industry processes and business needs at all times. The service is available to storage and data protection systems through a set of APIs that will enable such compliance be achieved and maintained with no user intervention and without labor-intensive manual work. The service will also allow storing the configuration of the data protection policies and create alerts when compliance changes. A data backup platform may include a data protection system that integrates with such a service and provides full regulatory/industry compliance.

Abstract: The management and backup of image and video media is automatically performed by evaluating a media file to characterize the content; transforming the media file, as by compressing it, based upon its evaluation and established policies and requirements; and storing the transformed media file with a high resolution in a storage tier having first access characteristics for a first retention period. Following the first retention period, the stored file is re-evaluated and further transformed and stored with lesser resolution in another tier having different access characteristics for a second retention period. Subsequently, the further transformed media file may be transformed again and stored in archive storage.