A modeling method and an apparatus are disclosed. The method includes: obtaining a first data set of a first indicator, and determining, based on the first data set, a second indicator similar to the first indicator; and determining a first model based on one or more second models associated with the second indicator. The first model is used to detect a status of the first indicator, and the status of the first indicator includes an abnormal state or a normal state. The second models are used to detect a status of the second indicator, and the status of the second indicator includes an abnormal state or a normal state.

Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value.

A system and method to capture and interact with a comprehensive digital record of an individual's biographical history and produce a synthetic model of their personality. The captured biographical history is a detailed record of this individual's actions, interactions, and experiences over a period which may span decades of their lifetime. The biographical history is indexed by areas of data variability and neural network confidence variability to identify points of likely human interest. A synthetic personality model is generated as a representation of the individual's personality structure, biases, sentiments, and traits. The synthetic personality can be interacted with through a digital interface and demonstrates the interaction patterns, triggers, and habits of the original individual. The functioning and the performance of the system over an individual's lifespan are optimized through data synthesis and disposition.

One example method includes receiving, by a telemetry collection manager from a telemetry consumer, brightness information concerning data accessed by the telemetry consumer, using, by the telemetry collection manager, the brightness information to determine a collection frequency for telemetry concerning the data, and transmitting, by the telemetry collection manager, telemetry collection frequency information to a telemetry generator. In this way, the telemetry consumer is able to control an amount and timing of telemetry generated by the telemetry generator.

Embodiments are disclosed for a data analysis tool for facilitating iterative and exploratory analysis of large sets of data. In some embodiments a data analysis tool includes a graphical user interface through which an interactive set of field identifiers is displayed. Each of the listed field identifiers may reference fields associated with a set of events returned in response to a search query, the set of events including machine data produced by components within an information technology (IT) environment that reflects activity in the IT environment. In response to user selections of field identifiers included in the displayed set, a data analysis tool may cause display of manipulable visualizations based on values included in fields referenced by the selected field identifiers.

A system and method for self-adjusting cybersecurity analysis and score generation, wherein a reconnaissance engine gathers data about a client's computer network from the client, from devices and systems on the client's network, and from the Internet regarding various aspects of cybersecurity. Each of these aspects is evaluated independently, weighted, and cross-referenced to generate a cybersecurity score by aggregating individual vulnerability and risk factors together to provide a comprehensive characterization of cybersecurity risk using a transparent and traceable methodology. The scoring system itself can be used as a state machine with the cybersecurity score acting as a feedback mechanism, in which a cybersecurity score can be set at a level appropriate for a given organization, and data from clients or groups of clients with more extensive reporting can be used to supplement data for clients or groups of clients with less extensive reporting to enhance cybersecurity analysis and scoring.

A labeling method includes determining whether there is an intersection between the first annotated segment and the second annotated segment; if Yes, determining whether the first annotated segment and the second annotated segment have different labels from each other; if Yes, sending the label of the first annotated segment to the second agent unit and the label of the second annotated segment to the first agent unit; if No, determining whether a discrepancy-over-union ratio between the first annotated segment and the second annotated segment is below a first threshold; if Yes, determining the intersection of the first annotated segment and the second annotated segment as a final annotated segment for the piece of time-series data; if No, assigning a review tag to a union segment of the piece of time-series data which has a duration from a start of the first annotated segment to an end of the second annotated segment.

A system and method for the detection and mitigation of data source compromises in an adversarial information environment. The system and method feature the ability to scan for, ingest and process, and then use relational, wide column, and graph stores for capturing entity data, their relationships, and actions associated with them. Furthermore, meta-data is gathered and linked to the ingested data, which provides a broader contextual view of the environment leading up to and during an event of interest. Data quality analysis is conducted on the data as it is ingested in order to identify various data source metrics and determine if a data source may be compromised. The results of the data quality analysis, the identified metrics, the gathered data, and meta-data are used to manage the reputation of the contributing data sources. The system can make recommendations on data sources based on the data source reputation scoring.

The technology relates to cosharding tables within a distributed storage system. A data table including one or more rows may be received. Each row in the data table may include an identifier key and pieces of data. Each piece of data in the data table may be indexed into individual rows of an index table, wherein each row in the index table includes data associated with the identifier key of the data table from which the piece of data in the respective row was indexed. The index table may be sharded into splits, wherein the sharding includes assigning each row of the index table into one of the splits based on the identifier key of the data table from which the piece of data in the respective row was indexed. The splits may be stored into two or more portions of the distributed storage system.

Techniques including data collection, organization and usage are provided, including in connection with computer-based gaming. Methods and systems are provided for establishing a set of data chronicling at least a portion of a duration of a computer-based gaming event that includes at least one user engaging in gaming using a computer or a computer-based device. Event data is obtained for chronicling chronologically ordered in-game events. Hardware and software related data is obtained that relates to the computer or the computer-based device and is relevant to the chronicling of the portion of the gaming event. Utilizing a distributed ledger technology or blockchain, the event data and the hardware and software related data are recorded in establishing the set of data chronicling at least a portion of the duration of the gaming event.