Abstract: Methods, systems, and computer program products for providing the status of model extraction in the presence of colluding users are provided herein. A computer-implemented method includes generating, for each of multiple users, a summary of user input to a machine learning model; comparing the generated summaries to boundaries of multiple feature classes within an input space of the machine learning model; computing correspondence metrics based at least in part on the comparisons; identifying, based at least in part on the computed metrics, one or more of the multiple users as candidates for extracting portions of the machine learning model in an adversarial manner; and generating and outputting an alert, based on the identified users, to an entity related to the machine learning model.

Abstract: A method, computer program, and computer system are provided for online fairness monitoring. A dataset having one or more entries with one or more protected attributes and data corresponding to a trained machine learning model is received. An entry having a maximum reward is selected based on a reward probability associated with the entry. A determination is made as to whether bias has developed in the trained machine learning model toward one or more of the one or more protected attributes based on a change to the reward probability or a distribution of reward probabilities exceeding a threshold value.

Abstract: The method performs at the orchestration interface at which update information, including changes to tasks of a workflow, is received from a task manager system (TMS), where the workflow includes a set of tasks, inputs to the tasks, and outputs from the tasks. The inputs and outputs determine runtime dependencies between the tasks. Based on the update information received, the orchestration interface populates a topology of nodes and edges as a directed acyclic graph (DAG) that maps nodes to tasks and edges to runtime dependencies between tasks, based on node inputs and outputs. The orchestration interface instructs the execution of the tasks and handling dependencies by interacting with a task execution system (TES) and by traversing the DAG, the orchestration interface identifies tasks that depend on completed tasks as per the runtime dependencies and instructs the TES to execute the dependent tasks identified.

Abstract: A method, computer system, and a computer program product for processing a computer dump by receiving at least one page of the computer system dump. The page includes a plurality of data tokens. The page may be parsed to extract a plurality of data tokens. The order of identifiers may be then determined for processing by using a probability sampling model. The probability sampling model calculates a plurality of reward based weights for each identifier using the tokens. The page may then be processed using the determined order of identifiers. The reward based weights may be updated after pages has been processed by determining frequency of each identifier detected during page processing.

Abstract: A computer-implemented method generates an automated data movement workflow. The method includes transforming a received request for data, which was received in a restricted natural language form, into a form suitable for accessing a metadata repository. The method further includes identifying data and data dependencies using the transformed request for data. The method further includes building a workflow using the identified data and data dependencies. The method further includes, upon applying at least one governance rule to the workflow, modifying the built workflow to be compliant with the at least one governance rule, and if no compliance with the at least one governance rule is achievable, recommending a change to the built workflow.

Abstract: Embodiments for identifying an optimal cloud computing environment for a computing task is disclosed. Embodiments comprises receiving a computing task to be executed in a cloud computing environment, wherein the computing task requires a set of cloud computing environment parameter values of the cloud computing environment, pre-selecting a set of candidate cloud computing environments, each of which meets the set of cloud computing environment parameter values, ranking the candidate cloud computing environments using reward-based ranking parameter values of the candidate cloud computing environments as an additional selection constraint, and selecting the highest ranking cloud computing environment as the optimal cloud computing environment for the computing task.

Abstract: One embodiment provides a computer implemented method, including: receiving, from a user, a natural language query for data contained within at least one data repository; identifying at least one concept from the natural language query, wherein the at least one concept includes an entity and an intent; identifying a plurality of datasets satisfying the natural language query by querying the at least one data repository utilizing the at least one concept; ranking the dataset based on relevance to the query; generating an extract-transform-load script that extracts, transforms, and loads a dataset selected by the user from the plurality of datasets; and retrieving data included in the dataset utilizing the extract-transform-load script, wherein the retrieving includes returning the data to the user.

Abstract: Methods, systems, and computer program products for identifying and redacting data from diagnostic operations via monitoring of data are provided herein. A computer-implemented method includes automatically monitoring data, which includes determining which portions of the data are accessed during a diagnostic operation; parsing an input file into portions of parsed data, wherein the input file comprises an initial output of the diagnostic operation; classifying the portions of parsed data into classes by applying at least one of multiple classification models to the parsed data, wherein the at least one classification model is specific to the accessed portions of data; automatically identifying sensitive data in the classified portions of parsed data by applying a class-to-sensitivity mapping technique to the classified portions of parsed data; redacting the identified sensitive data from the input file; and generating and outputting an updated output of the diagnostic operation based on the redacting.

Abstract: Methods, systems, and computer program products for generating a data migration plan for in-place encryption of data are provided herein. A computer-implemented method includes receiving, from a user, a request to generate a migration plan for performing in-place encryption of data within a database, wherein the migration plan indicates periods of time in which portions of the data are to be encrypted; determining a set of constraints for performing the in-place encryption; generating the migration plan based at least in part on the set of constraints; and performing the in-place encryption of the data in accordance with the migration plan such that only a single copy of each of the portions is maintained during the in-place encryption, wherein the single copy comprises one of a plaintext copy of data corresponding to the portion, and an encrypted copy of data corresponding to the portion.

Abstract: One embodiment provides a method, including: receiving, from a user, a dataset for encryption before its storage at a data storage location, wherein the dataset comprises a plurality of portions; identifying (i) attributes of the dataset and (ii) dataset dependencies; generating a recommendation for an encryption scheme to be used for the dataset, wherein the generating comprises (i) generating, based upon the attributes and the dataset dependencies, a recommendation of an encryption scheme for each portion of the dataset and (ii) identifying, based upon the dataset dependencies, a key label for each portion of the dataset, wherein the key label identified for a portion of the dataset that is dependent on another portion of the dataset is the same as the key label identified for said another portion of the dataset; and providing, to the user, (i) the generated recommendation and (ii) a description identifying reasons for the generated recommendation.

Abstract: One embodiment provides a computer implemented method, including: receiving, from a user, a natural language query for data contained within at least one data repository; identifying at least one concept from the natural language query, wherein the at least one concept includes an entity and an intent; identifying a plurality of datasets satisfying the natural language query by querying the at least one data repository utilizing the at least one concept; ranking the dataset based on relevance to the query; generating an extract-transform-load script that extracts, transforms, and loads a dataset selected by the user from the plurality of datasets; and retrieving data included in the dataset utilizing the extract-transform-load script, wherein the retrieving includes returning the data to the user.

Abstract: A method for automatically generating documentation for an artificial intelligence model includes receiving, by a computing device, an artificial intelligence model. The computing device accesses a model facts policy that indicates data to be collected for artificial intelligence models. The computing device collects artificial intelligence model facts regarding the artificial intelligence model according to the model facts policy. The computing device accesses a factsheet template. The factsheet template provides a schema for an artificial intelligence model factsheet for the artificial intelligence model. The computing device populates the artificial intelligence model factsheet using the factsheet template with the artificial intelligence model facts related to the artificial intelligence model.

Abstract: Methods, systems, and computer program products for dynamically analyzing diagnostic operations data via machine learning techniques are provided herein. A computer-implemented method includes defining aspects of machine learning techniques to be performed in connection with diagnostic operation data analysis, including: defining dynamic analysis granularity selection functionality based on time constraints and the level of progress of the analysis; defining dynamic data classification identifier type selection functionality based on the time constraints and the level of progress of the analysis; and defining dynamic ordering of data classification identifiers during runtime based on data classification preferences, information pertaining to system workload, and information pertaining to requested analysis compliance parameters.

Abstract: Methods, systems, and computer program products for generating a data partitioning strategy for secure and efficient query processing are provided herein. A computer-implemented method includes obtaining at least (i) a database schema associated with a database and (ii) a query workload associated with the database; and generating, based at least in part on the database schema and the query workload, a distributed database structure for the database that (i) stores a first set of columns of the database within a private cloud environment in a plaintext format and (ii) stores a second set of columns of the database in a public cloud environment, wherein the second set of columns is stored in either a plaintext format or an encrypted format based on whether the second set of columns comprises sensitive data.

Abstract: Methods, systems, and computer program products for dynamically managing predicate expression columns in an encrypted database are provided herein.

Abstract: A method for automatically generating documentation for an artificial intelligence model includes receiving, by a computing device, an artificial intelligence model. The computing device accesses a model facts policy that indicates data to be collected for artificial intelligence models. The computing device collects artificial intelligence model facts regarding the artificial intelligence model according to the model facts policy. The computing device accesses a factsheet template. The factsheet template provides a schema for an artificial intelligence model factsheet for the artificial intelligence model. The computing device populates the artificial intelligence model factsheet using the factsheet template with the artificial intelligence model facts related to the artificial intelligence model.

Abstract: Methods, systems, and computer program products for generating a data partitioning strategy for secure and efficient query processing are provided herein. A computer-implemented method includes obtaining at least (i) a database schema associated with a database and (ii) a query workload associated with the database; and generating, based at least in part on the database schema and the query workload, a distributed database structure for the database that (i) stores a first set of columns of the database within a private cloud environment in a plaintext format and (ii) stores a second set of columns of the database in a public cloud environment, wherein the second set of columns is stored in either a plaintext format or an encrypted format based on whether the second set of columns comprises sensitive data.

Abstract: Methods, systems, and computer program products for identifying and redacting data from diagnostic operations via monitoring of data are provided herein. A computer-implemented method includes automatically monitoring data, which includes determining which portions of the data are accessed during a diagnostic operation; parsing an input file into portions of parsed data, wherein the input file comprises an initial output of the diagnostic operation; classifying the portions of parsed data into classes by applying at least one of multiple classification models to the parsed data, wherein the at least one classification model is specific to the accessed portions of data; automatically identifying sensitive data in the classified portions of parsed data by applying a class-to-sensitivity mapping technique to the classified portions of parsed data; redacting the identified sensitive data from the input file; and generating and outputting an updated output of the diagnostic operation based on the redacting.

Abstract: Methods, systems, and computer program products for dynamically analyzing diagnostic operations data via machine learning techniques are provided herein. A computer-implemented method includes defining aspects of machine learning techniques to be performed in connection with diagnostic operation data analysis, including: defining dynamic analysis granularity selection functionality based on time constraints and the level of progress of the analysis; defining dynamic data classification identifier type selection functionality based on the time constraints and the level of progress of the analysis; and defining dynamic ordering of data classification identifiers during runtime based on data classification preferences, information pertaining to system workload, and information pertaining to requested analysis compliance parameters.

Abstract: Methods, systems, and computer program products for dynamically managing predicate expression columns in an encrypted database are provided herein.