Abstract: Systems and methods described herein relate to the efficient handling of data purge requests in the context of a distributed storage system. A plurality of data purge requests is stored in a first data structure. The data purge requests may be grouped into batches that are processed at least partially in parallel. A first data purge request from the plurality of data purge requests is successfully processed, and is moved from the first data structure to a second data structure. Processing of a second data purge request from the plurality of data purge requests is unsuccessful. The second data purge request is retained in the first data structure. Purge status data is generated based on the first data purge request being in the second data structure and the second data purge request being in the first data structure. The purge status data may be presented at a user device.

Abstract: A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

Abstract: Techniques for leveraging efficient metadata communications to improve domain name system (DNS) security are described. The DNS service uses a hash value to uniquely identify a client, and detect any change in metadata in order to keep policies up-to-date for the client. In an example method a first DNS query for a client device is intercepted. A cryptographic hash function is applied to metadata associated with the client device to generate a hash value. The hash value is added to an additional records section of the first DNS query to generate a second DNS query. The second DNS query is transmitted to a DNS service. The metadata associated with the client device is transmitted to the DNS service on an out-of-band encrypted channel. A DNS response, including the hash value, is received from the DNS service and transmitted to the client device.

Abstract: There is disclosed in one example a network interface card (NIC), comprising: an ingress interface to receive incoming traffic; a plurality of queues to queue incoming traffic; an egress interface to direct incoming traffic to a plurality of server applications; and a queuing engine, including logic to: uniquely associate a queue with a selected server application; receive an incoming network packet; determine that the selected server application may process the incoming network packet; and assign the incoming network packet to the queue.

Abstract: Comprehensive matching allows for automated conversion from runtime policy rules to build time rules that can be applied to an IaC configuration file(s). API specifications of a CSP and resource models defined in an IaC configuration file(s) are parsed and tokenized. The tokenized API specifications are evaluated to identify, for each resource model, a most appropriate API specification for mapping fields. Based on the evaluation and token matching, tokens of the API specifications are mapped to the tokens of the IaC resource models to form a mapping model. In an implementation phase, a runtime policy rule converter replaces tokens of a runtime security policy rule query with IaC tokens based on the mapping index to convert the runtime security policy rule query into a buildtime security policy rule query that can be applied against the IaC configuration files.

Abstract: A method and apparatus for updating data router nodes in a distributed storage system are described. The method can include querying, by a first database agent of a database node, a cache data store for health status metrics of the cache data store. The method can also include storing, by the first database agent of the database node, the health status metrics in a data repository. Furthermore, the method can include obtaining, by a second database agent of a router node, the health status metrics from the data repository, and updating, by the second database agent of the router node, a database topology file based on the health status metrics.

Abstract: Systems, devices, and techniques are disclosed for data shards for distributed processing. Data sets of data for users may be received. The data sets may belong to separate groups. User identifiers in the data sets may be hashed to generate hashed identifiers for the data sets. The user identifiers in the data sets may be replaced with the hashed identifiers. The data sets may be split to generate shards. The data sets may be split into the same number of shards. Merged shards may be generated by merging the shards using a separate running process for each of the merged shards. The merged shards may be generated using shards from more than one of the two or more data sets. An operation may be performed on all of the merged shards.

Abstract: In response to determining that continuous data protection is to be enabled for a particular table of a database service, a service component verifies that automated transmission of change records of the table to a log-structured journal has been configured. A given change record comprises a before-image and an after-image associated with a committed database write, and is assigned a unique sequence number. In response to a determination to restore the table as of a specified point in time, a restore record set is identified from the journal with respect to a selected snapshot of the table. The restore record set includes change records which are not represented in the snapshot and are to be represented in the restored table. A restore result table is created using the selected snapshot and the restore record set.

Abstract: Techniques are provided for facilitating network devices to obtain configuration updates from a central configuration repository. Configuration update information is received regarding a configuration update in a configuration repository. A data tree is updated based on the configuration update information. An identifier unique to the update is generated. A determination is performed that network device properties of a network device correspond to a set of network device properties indicated for the configuration update information. A notification indicating the availability of the configuration update is sent over one or more networks to the network device.

Abstract: A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

Abstract: Technologies are described herein for media content recommendations. For example, a method of media content recommendations may include generating, by a plurality of machine learning algorithms, a first set of media content recommendations, a second set of media content recommendations, and a third set of media content recommendations. The method may also include generating a first playlist based on the first set of media content recommendations and the second set of media content recommendations, generating a second playlist based on the second set of media content recommendations and the third set of media content recommendations, and providing the first playlist and the second playlist to at least one of the one or more media applications.

Abstract: An apparatus may be configured to determine an industry object model for a data set of an enterprise; and generate an archive package for an archive time point by generating a set of global objects such that each global objects of the set of global objects is represented in the data set and for a respective data source of the set of data sources, generating a set of data source objects based on the industry object model, associating the set of data source objects with the set of global objects, and storing, in the archive package, the set of data source objects and the associated global objects for the respective data source.

Abstract: A method for file locks in a distributed file system, performed by a storage system is provided. The method includes receiving, at a storage system having a distributed file system, a request for access of a file and locking the file, through one of a plurality of persistent file locks in the storage system. The method includes accessing the file, through the distributed file system, and unlocking the file, through the one of the plurality of persistent file locks.

Abstract: Systems are provided for generating, modifying and using SBOMs for facilitating risk assessment and threat mitigation for corresponding programs, and particularly for large programming builds. The creation and modification of the SBOMs includes processes for omitting declarations referenced in chunk SBOMs of program chunks incorporated into a final programming build associated with a build SBOM, but which are not actually utilized by the final programming build, as well as processes for adding new declarations for code segments that are not declared in the related chunk SBOMs, even though the code segments are utilized by the final programming build. Systems are also configured to use SBOMs in combination with configuration restriction records to assess and resolve threat events in a manner that can prevent unnecessary remedial actions for threat events that appear to be relevant to one or more files or dependencies incorporated into a program.

Abstract: Disclosed herein are an apparatus and method for managing integrated storage. The apparatus includes a data distribution and storage unit for distributing data in order to store the data in integrated storage, including on-premises storage and cloud storage; a storage management unit for connecting to the integrated storage in order to store the data and providing information about storage tiering pertaining to the data; a data manipulation unit for providing the integrated storage as virtual data storage regardless of a location at which the data is actually stored; and a storage connection unit for providing a user with an interface for the created virtual data storage as a single virtual storage unit, wherein the information about storage tiering varies depending on the performance of storage, the time during which the data is used, and the frequency with which the data is accessed.

Abstract: This application relates to apparatus and methods for identifying and remediating poor user experiences on computing devices. In some examples, a user speed determination device is configured to receive a content delivery request for delivery of content to a user device. The computing is also configured to obtain user identification data, obtain user device data and determine a user device speed based on the user identification data and the user device data. The computing device then sends a user device speed indicator to a content delivery device to cause the content delivery device to deliver remediated content to the user device when the user device speed is determined to be less than a predetermined speed threshold. The user identification data can include an IP address and the user device data can include user agent data, user connection data and user resource timing data.

Abstract: An intent decomposition method includes sending, by a first network device, a first sub-intent target value to a second network device. The method also includes receiving, by the first network device, a first message from the second network device. The first message is used to indicate that the first sub-intent target value is not achieved by the second device. The first message includes a first measurement value of the second network device. The method further includes re-decomposing, by the first network device, an intent based on the first measurement value, and sending first sub-intent target values obtained through re-decomposition to the second network device and one or more other network devices different from the first network device and the second network device until all the first sub-intent target values obtained through re-decomposition are achieved or none of the first sub-intent target values obtained through re-decomposition are achieved.

Abstract: A data storage system includes a tuner that obtains data samples for data storage operations of workloads and calculates feature measures for a set of features of the data storage operations over aggregation intervals of an operating period. It further (1) applies a cluster analysis to the feature measures to define a set of clusters, and assigns the feature measures to the clusters, and (2) applies a classification analysis to the feature measures labelled by their clusters to identify dominating features of each cluster, and generates workload profiles for the clusters based on the dominating features, and then automatically adjusts configurable processing mechanisms (e.g., caching or tiering) based on the workload profiles and performance or efficiency goals.

Abstract: Artificial Intelligence-based (AI-based) modeling can be used to predict “Critical Times” when “bottlenecks” in a processing of data would occur. Moreover, for each one of the predicted Critical Times, it can be determined which one of multiple Computing Resources would cause the bottleneck, so that more precise measures can be taken and taken before a Critical Time, in an effort to prevent bottlenecks from happening in computing systems, especially more complex database systems with more demeaning service needs and requirements.

Abstract: A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

Abstract: A computer-implemented method can receive a hierarchy table comprising a plurality of records associated with objects organized in a hierarchical structure. The records comprise values corresponding to a plurality of displayable fields and specify value distributions among the objects. The method can specify one or more viewable fields at an input area of a graphical user interface, and display a plurality of nodes and a plurality of directional links connecting the displayed nodes on a display window of the graphical user interface. The displayed nodes represent objects whose associated records have unique combinations of values corresponding to the specified viewable fields. The directional links represent value distributions among objects represented by the displayed nodes. The method can display aggregated value distributed to or from objects represented by the displayed nodes. The viewable fields specify which of the displayable fields are visible on the displayed nodes.

Abstract: Systems and techniques for metadata quality monitoring and remediation are described herein. Metadata is obtained from a system of record. The metadata is normalized. The metadata is evaluated with an integrity rule to identify a discrepancy in an element of the metadata. The discrepancy is stored as an integrity gap in an integrity database. A notification is generated that includes identification of the element of the metadata and a description of the integrity rule. The notification is transmitted to a user identified based on the integrity rule.

Abstract: Whether a document file is tampered and the like can be determined without imposing a burden on a user. A hash value calculation unit 103 adds contents of update to an original document as incremental update in order of update, and calculates a hash value of the document file for each of the original document and a document for adding the updated content and a hash value of a document file the hash value and the document file ID, identifying the document file, of which are registered in a blockchain network. An ID acquisition unit 102 acquires the document file ID identifying a received document file, from the document file. A hash value acquisition unit 105 acquires the hash value stored in the latest block among blocks storing the document file IDs from the blockchain network. A tampering determination unit 106 determines whether the document file is tampered by determining whether the hash value calculated and the hash value acquired from the blockchain network 300 match.

Abstract: Aspects related to a resource-constrained system are described herein that can provide object storage services after a service interruption is resolved, even if all of the transactions that were pending and incomplete prior to the service interruption have not yet been recovered and/or executed. For example, file systems implemented by computing systems of the resource-constrained system may treat each file or directory as a separate object. Thus, a transaction directed to one file may not affect the file's directory or other files in the directory. As a result, the resource-constrained system can achieve read-after-write consistency without first recovering and executing the pending, incomplete transactions. Instead, read-after-write consistency for an object can be achieved simply by completing any pending, incomplete transaction directed to that object.

Abstract: Automated negotiation agent adaptation is performed by detecting change in a utility function involved in automated negotiation between a supporting agent and an opposing agent while the supporting agent operates according to a first negotiation strategy model, generating a plurality of training samples from automated negotiation between the supporting agent and the opposing agent while the supporting agent operates according to a baseline negotiation strategy model, and training an initialized negotiation strategy model using the plurality of training samples to produce a second negotiation strategy model.

Abstract: A hospital or laboratory network including analytical devices for performing in-vitro diagnosis and a gateway is proposed. The network is configured to send a data package request including information regarding the analytical devices from the gateway to a remote service platform, receive from the remote service platform information regarding available data packages, determine a selection of the available data packages to be downloaded from the remote service platform specific to the analytical devices in the network, request the selection of the available data packages from the remote service platform, download the requested selection of the available data packages from the remote service platform, and provide the requested selection of the available data packages to the analytical devices.

Abstract: A query is preprocessed for features identified by a Data Manipulation Language (DML) in the text of the query. A machine-learning algorithm uses the features as input and provides as output a predicted query parsing execution time needed by a query parser to parse the query. The predicted query parsing time is provided as input to a query optimizer. The query optimizer uses the predicted query parsing time as a factor in optimizing a query execution plan for the query. Subsequently, the query execution plan is executed against a database as the query.

Abstract: A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

Abstract: Provided is a system for facilitating recovery of deleted computing resources in a cloud network environment. A centralized resource recovery service may be in network communication with a plurality of resource management services that are each configured to create, modify, or delete their respective computing resources such as data storage volumes, databases, compute instances, and the like. The resource recovery service may be configured to receive a delete request associated with a resource managed by one of the resource management services, and cause the resource to be retained in a recovery bin based on the resource satisfying one of a plurality of resource recovery conditions used to manage resource recovery across the resource management services.

Abstract: A method for protecting a client domain, for example against a computing attack, implemented in a client node of the client domain. The method includes: discovering at least one other client node of the client domain, called a discovered node; detecting a conflict between at least two management rules for the traffic associated with the client domain; and resolving the detected conflict, including: if one of the rules was installed by a the discovered node, modifying the rule or a state associated with the discovered node; and otherwise, obtaining, from a the discovered node, an item of information for identifying at least one node of the client domain that installed one of the rules; and detecting and/or resolving the conflict using information obtained during the discovery of the at least one other node of the client domain.

Abstract: A computer implemented method for the automated analysis or use of data is implemented by a voice assistant. The method comprises the steps of: (a) storing in a memory a structured, machine-readable representation of data that conforms to a machine-readable language (‘machine representation’); the machine representation including representations of user speech or text input to a human/machine interface; and (b) automatically processing the machine representations to analyse the user speech or text input.

Abstract: Provided is a storage system capable of properly deleting derivative data stored at a plurality of sites. A CPU executes a creation process of creating data based on data stored in a storage device at a local site and storing the created data in the storage device of a node at one of the plurality of sites. Further, the CPU collects, from each of the plurality of sites, history information created at each of the plurality of sites to indicate the history of each creation process. When deleting deletion-specified data, the CPU identifies deletion derivative data according to the history information created at each of the plurality of sites, and deletes the deletion-specified data and the deletion derivative data from the storage device at each of the plurality of sites. The deletion derivative data is derivative data derived from the deletion-specified data.

Abstract: An image forming apparatus includes an operation device; a storage that stores classification determination information and a user classification rule; a memory that stores instructions; and a processor. The processor executes the instructions stored to: input image data on a document; acquire the input image data on the document; acquire, from the acquired image data, feature quantity; and update the user classification rule. The user classification rule is information in which a criterion for classifying a document having specific feature quantity is set for each user in association with the specific feature quantity. When the user uses the operation device to perform a specific classification operation on image data on a document having the acquired feature quantity, the processor executes the instructions to change a criterion of the user classification rule of the user associated with the acquired feature quantity to a criterion corresponding to the specific classification operation.

Abstract: This disclosure relates to method and system for identifying Personally Identifiable Information (PII) through secret patterns. The method includes receiving user data from at least one data source through a plurality of communication channels. The user data includes PII and non-PII. The user data is associated with a user. The PII includes a plurality of personal identifiers. The method further includes identifying the PII in user data through a predictive model. The method further includes generating a secret pattern based on the PII identified through the predictive model. The secret pattern is an identifiable label. The method further includes adding the secret pattern to each of the plurality of personal identifiers in PII. The method further includes identifying each of the plurality of personal identifiers through the secret pattern in real-time, when user data is transmitted from the at least one data source to at least one data destination.

Abstract: A processing system including at least one processor may obtain a first ontology of a first type of data pipeline component, map the first ontology to a second ontology for a second type of data pipeline component that is stored in a catalog of data pipeline component types, provide a second data schema for the second type of data pipeline component as a template for a first data schema for the first type of data pipeline component, and add the first type of data pipeline component to the catalog of data pipeline component types, where the adding comprises storing the first ontology and the first data schema for the first type of data pipeline component in the catalog of data pipeline component types.

Abstract: The technology disclosed relates to endpoint data loss prevention (DLP). In particular, the technology disclosed relates to enforcing data loss prevention policies at an endpoint without needing to perform content sensitivity scan at the endpoint.

Abstract: A file management device comprising a memory; and a processor coupled to the memory and the processor configured to: a common feature extracting unit that extracts a feature common to a plurality of data files to which a same tag is provided from the data files; a tagging rule storage DB that stores a feature extracted by the common feature extracting unit and the tag provided to the data files in association with each other as a tagging rule; and a tag providing unit that provides a tag to a newly input data file based on the tagging rule stored in the tagging rule storage DB.

Abstract: In some implementations, a device may receive a request to merge a first cloud computing instance with a second cloud computing instance to generate a multi-cloud computing instance. The device may access a first application programming interface to obtain a first configuration of the first cloud computing instance. The device may access a second application programming interface to obtain a second configuration of the second cloud computing instance. The device may generate a target configuration based on the first configuration or the second configuration. The device may instantiate a set of resources with the target configuration for the multi-cloud computing instance. The device may provide output identifying the multi-cloud computing instance.

Abstract: A search query relating to a search for people and including one or more search terms is received. A search graph for the search is created from a previously created graph which is a directional graph in which people are represented by nodes and content is represented by nodes or edges. The search graph is generated by filtering out nodes or edges that represent content that is determined not to be relevant to the search terms in the search query; and, for the remaining content that is determined to be relevant to the search terms in the search query, adding to the graph a measure of the relevance of the content to the search terms. The search results are generated by operating on the search graph to identify people in the search graph who are sources of content that is relevant to the search terms.

Abstract: Systems, devices, and methods are provided for determining whether security assurances are satisfied by security policies that are used to control access to resources used by a mainframe application. A system may use a database to store a plurality of security policies that may comprise security polices of various resources used by mainframes, including resources managed by operating systems and database systems. A reference policy that corresponds to the security assurance being sought may be determined. The security policies may be evaluated using a satisfiability modulo theories (SMT) solver to determine whether the security policies are equally or less permissive than the reference policy.

Abstract: Various techniques are described for platform management of integrated access of public and privately-accessible datasets utilizing federated query generation and query schema rewriting optimization, including receiving at a dataset access platform a query formatted according to a first data schema, generating a copy of the query, saving the query and the copy to a datastore, parsing the copy of the query in the first schema using an inference engine, determining whether the query comprises data associated with an access control condition associated with accessing the dataset, the access control condition being configured to indicate whether the query is permitted to access the dataset, and rewriting, using a proxy server, the copy of the query in a second schema, and optimizing the rewriting by identifying a database engine to execute the query and including other data converted into another triple associated with an attribute of the query.

Abstract: Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.

Abstract: Various techniques are described for platform management of integrated access of public and privately-accessible datasets utilizing federated query generation and query schema rewriting optimization, including receiving at a dataset access platform a query formatted according to a first data schema, generating a copy of the query, saving the query and the copy to a datastore, parsing the copy of the query in the first schema using an inference engine, determining whether the query comprises data associated with an access control condition associated with accessing the dataset, the access control condition being configured to indicate whether the query is permitted to access the dataset, and rewriting, using a proxy server, the copy of the query in a second schema by converting the copy of the query into a triple associated with the query and another triple associated with the access control condition.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive structural analysis using at least one of table column classification machine learning models, table column clustering machine learning models, structural variance generation machine learning models, and emergence report generation machine learning models.

Abstract: Provided herein are systems and methods for identity resolution and data enrichment. An example method performed by at least one hardware processor includes detecting at an account of a data provider, an update to personally identifiable information (PII). The PII is stored in a source table managed by an account of a data consumer. An identity resolution process is performed based on detecting the update. The identity resolution process includes generating a secure identifier of a user associated with the PII. The method further includes generating at the account of the data provider, a result table including the secure identifier. The result table is shared with the account of the data consumer.

Abstract: The present disclosure relates to a non-transitory computer readable medium for a separate context viewing, organization, and management area for annotations that have been created. The rationale for such computer readable medium is discussed in detail. These annotations can be created on webpages or PDF documents available at a uniform resource locator (URL) anywhere on the World Wide Web. Once these annotations are created, having a system to manage the life cycle of these annotations in various contexts separate from the original web page is beneficial. This annotation life cycle and the rationale for various steps within this life cycle is discussed in detail. The present disclosure also describes some pertinent filtering and display technologies for annotations that have been created.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a metadata model definition comprising a set of entity definitions specifying a set of entities, a set of semantic key definitions specifying a set of semantic keys associated with the set of entities, and a set of relationship definitions specifying a set of relationships between the set of entities. The set of semantic keys are configured to be used by an application to refer to the set of entities. The program further determines a set of technical keys for the set of entities. The set of technical keys are configured to be used by the device to refer to the set of entities. The program also stores the metadata model definition and the set of technical keys in a set of records.

Abstract: Techniques are disclosed for performing operations in a distributed computing environment comprising a plurality of computing devices implementing a Kubernetes environment. An indication is received of one or more custom resources of the Kubernetes environment. The custom resources are grouped into a commit set. The commit set is defined as an atomic unit which either succeeds or fails atomically. It is determined that at least one of the custom resources has failed to complete. In response to the determination, the custom resources of the commit set are reverted to a previous consistent state.

Abstract: A system and method for generating shard data based on semantic sharding is proposed. Shard data is generated by a map sharder that is configured to generate the shard data based on semantic objects in a geographical area and a definition of sections. The sections cover parts of the geographical area. The map sharder searches, for each of the sections, for semantic objects that are located at least partly in a section and stores found objects in a shard data entry of the shard data.

Abstract: A method and system for cloud distributed hybrid data storage and normalization are disclosed. The method may include obtaining a data set comprising data entities. A data entity may comprise data fields each containing a data element. The method may further include determining policy constraint meta-data for each of the data elements based on the storage policy constraint. The policy constraint meta-data may include a first meta-tag indicating the storage policy constraint for the data element. The method may further include determining whether a server satisfies the storage policy constraint based on the first meta-tag for the data element. When the server satisfies the storage policy constraint, the method may further include transmitting the data element to the server to store the data element on the server. When the server fails to satisfy the storage policy constraint, the method may further include, storing the data element on the client.