Abstract: A computer implemented method manages an artificial intelligence model. A number of processor units detect a change in a format used to exchange information between the artificial intelligence model and an application using the artificial intelligence model. The number of processor units changes the format of the information into an expected format used by the artificial intelligence model and the application. The number of processor units exchanges the information between the artificial intelligence model and the application using the expected format.

Abstract: A software defined data security level method, computer program product, and data processing system. One embodiment may comprise intercepting, by a processor at a data security layer, an input/output (IO) request from a local software application, wherein the IO request includes a header and a data payload, analyzing, by the processor at the data security layer, the data payload of the IO request relative to a service level agreement (SLA), assigning, by the processor at the data security layer, a security level to the IO request based on the analysis.

Abstract: Application-specific prioritization of streaming data replication. Data streamed from connected devices is selectively replicated to data storage clusters based on needs of the applications being served by the data. Data characterization supports prioritized replication processing. Statistical metrics compare streaming data with estimated values to characterize the data for prioritization.

Abstract: Embodiments relate to a system, computer program product, and method for determining shelter areas for two-wheeler vehicles, and, more specifically, for dynamically distinguishing the behavior of two-wheeler vehicles and non-two-wheeler vehicles as an indicator of shelter areas from inclement weather. The behavior of the vehicles is distinguished through a plurality of two-wheeler vehicles slowing down and congregating at a particular location as a shelter against inclement weather, while non-two-wheeler vehicles may slow down, however, not stop proximate this location.

Abstract: Aspects of the present invention disclose a method for dynamic password inducing techniques for security configuration and validation of a user. The method includes one or more processors identifying textual data of a user. The method further includes generating a set of password parameters for a password. The method further includes identifying one or more password dynamisms of the user from one or more sources, where the one or more password dynamisms are dynamic inputs, from the user, to an authentication device. The method further includes modifying the textual data to include a text placeholder, wherein the text placeholder includes a replacement parameter that induces the user to provide a password dynamism. The method further includes configuring the set of password parameters for the password of the user based at least in part on the one or more password dynamisms of the user from the one or more sources.

Abstract: In an approach for bypassing security vulnerable and anomalous devices in a multi-device workflow, a processor monitors behavior and network traffic of a plurality of smart devices within a multi-smart device system. A processor identifies a first smart device of the plurality of smart devices with at least one of a security vulnerability and an anomaly. A processor identifies a multi-smart device workflow that includes the first smart device. A processor identifies a function of the first smart device within the multi-smart device workflow. A processor determines whether an alternative smart device can replace the first smart device within the multi-smart device workflow. Responsive to resolution of the at least one of the security vulnerability and the anomaly, a processor re-establishes the workflow with the first smart device.

Abstract: A method, computer system, and a computer program product for image protection are provided. A first device includes a computer and a first camera. The first device identifies a picture that has a hallmark. The first device transmits a message requesting authorization to have a copy of the picture. The message contains data representative of the hallmark. The first device receives a response message. The first device determines whether the response message authorizes capture of a copy of the picture.

Abstract: A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to run a machine learning base model on input data to generate base model prediction data and run a machine learning error prediction model on the input data to generate error prediction data. The at least one processor is configured to execute the instructions to generate predicted correct base model prediction data based on the base model prediction data and the error prediction data. The at least one processor is configured to execute the instructions to generate confusion values data based on the base model prediction data and the predicted correct base model prediction data. The at least one processor is also configured to execute the instructions to generate base model accuracy fairness metrics data based on the confusion values data.

Abstract: Embodiments relate to a system, program product, and method for generating an enhanced feature catalog for a predictive model. The embodiments disclosed herein include capturing predictive model design time information including training data lineage metadata to determine the features of the training data, model design time measurements, and model design time metadata. Once the predictive model is built, the training data lineage metadata is used to capture the features that will be maintained within a feature catalog. The model design time measurements and model design time metadata provide further correlation between the predictive model and the features. Runtime metrics on the predictive model create additional correlations between the captured data and metadata with the features in the feature catalog to expeditiously identify the relevant features of the predictive model.

Abstract: One example of a method comprises identifying a model to be validated that is stored in a repository; automatically computing and recording one or more model metrics for the model to be validated in a tamper-proof manner; comparing the computed tamper-proof metrics with one or more encoded rules and policies to determine if the model to be validated complies with the one or more encoded rules and policies; and outputting a notification to a device indicating a validation status of the model to be validated based on the comparison of the computed tamper-proof metrics with the one or more encoded rules and policies.

Abstract: Methods, systems, and computer program products for determining data representative of bias within a model are provided herein. A computer-implemented method includes obtaining a first dataset on which a model was trained, wherein the first dataset contains protected attributes, and a second dataset on which the model was trained, wherein the protected attributes have been removed from the second dataset; identifying, for each of the one or more protected attributes in the first dataset, one or more attributes in the second dataset correlated therewith; determining bias among at least a portion of the identified correlated attributes; and outputting, to at least one user, identifying information pertaining to the one or more instances of bias.

Abstract: In an approach to facilitate contactless remote shopping assistance, a computer-implemented method includes one or more processors configured for receiving first order data from a user device corresponding to an order of items to be retrieved from a parking lot of a retail entity proximate to a retail entity location, transmitting the first order data to the retail entity, and assigning the order to a mobility device stationed at the retail entity. The method further includes transmitting order retrieval instructions to the mobility device causing the mobility device to navigate the retail to secure the items, receiving an indication that the mobility device secured the items, and transmitting order delivery instructions to the mobility device. The method further includes receiving a second indication that the mobility device transported the items to the parking lot and placed the items in a vehicle associated with a user of the user device.

Abstract: Disclosed embodiments provide techniques for monitoring application program interface (API) health based on design-time checks and runtime performance. The health of an API can include multiple factors. The factors may include correctness of the data returned/output by the API. A high amount of incorrect data may correlate to a lower health metric. A low amount of incorrect data may correlate to a higher health metric. If a health metric value falls below a predetermined threshold, it may indicate that the API health is poor, and hence, should not be used, or should be used with caution, depending on the application. In embodiments, an alternate API may be automatically selected as a replacement for an API in response to a health metric falling below a predetermined threshold.

Abstract: An artificial intelligence model that performs operating the artificial intelligence model, which data taken collectively is uncollected payload data, storing the uncollected payload data to obtain a collected payload data set in the form of a plurality of data points, clustering the plurality of data points of payload data, calculating an average feature distance, calculating average label distance, grouping all given pairs of data points, and determining a plurality of close pairs of data points.

Abstract: An approach is disclosed that inputs data points to a trained artificial intelligence (AI) model with an outlier model that identifies data points on which the AI model has been trained. A value is received from the outlier model corresponding to each of the data points with the received value being a prediction of whether the AI model has been trained on the respective data point. A bias analysis is performed on the trained AI model using a subset of the data points that received a prediction that indicates that the trained AI model was trained with the respective data point.

Abstract: A system and method is provided to selectively process and store tables of a relational database by calculating an overall data sensitivity score for each table based on predefined attribute rules; performing column-wise splitting of at least one of the tables into a first table and a second table based on the overall data sensitivity score of each table, thereby generating a total number of relational database tables; storing a first subset of the total number of relational database tables in a private cloud storage database in a distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables; and storing a second subset of the total number of relational database tables in a public cloud storage database of the distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables.

Abstract: In an approach, a processor receives a request to access an electronic resource from a device. A processor causes the device to generate a Completely Automated Public Turing test (CAPTCHA), where the CAPTCHA comprises: a virtual keyboard; an ordered string of characters required to be input; and presentation of a highlighted key of the virtual keyboard on the device, wherein (i) the highlighted key is a first key visually distinct from other keys of the virtual keyboard and (ii) the first key corresponds to a character of the ordered string of characters. A processor receives a result of the CAPTCHA from the device. A processor performs an action based on the result.

Abstract: Information associated with a user and a presentation made by the user is received. A presentation readiness of the user is dynamically detected. One or more of a presentation mode of a presentation software and a recording mode of the presentation software is initiated based on the received information and the dynamically detected presentation readiness.

Abstract: A processor may receive, by a computing device, the indirect command from a user. The indirect command may include an instruction to the computing device to collect an information dataset from a secondary source. A processor may analyze the information dataset from the secondary source. A processor may determine one or more actions to be performed. The one or more actions may be based, at least in part, on the information dataset from the secondary source. A processor may execute the one or more actions.

Abstract: A computer-implemented method includes: receiving, by a computing device and from a user device, a request to validate an application program interface (API); validating, by the computing device, the API by performing a fetch analysis using different user profiles; returning, by the computing device and to the user device, a result of the fetch analysis; validating, by the computing device, the API by performing an insert/update analysis using the different user profiles; and returning, by the computing device and to the user device, a result of the insert/update analysis