International Business Machines Corporation

Kyndryl, Inc.

Krzysztof A Rudek

Vinod A Valecha

Grzegorz Piotr Szczepanik

Lukasz Jakub Palus

Tomasz Hanusiak

Konrad Wojciech Komnata

Chitra A Iyer

Markus Blohberger

Angelika Kozuch

Tiago Pagani

Michal Bodziony

Pablo R M Gonzalez

Bartosz Tomasik

Jaroslaw Jurowicz

Wojciech A Wojcik

Pablo Roberto Millicay Gonzalez

A method includes providing a relational database and at least one schema describing tables of the relational database with columns of the relational database, providing an application executing read/write or delete jobs in the relational database where the application is running in a cloud environment, upgrading the application running in the cloud environment to a new version of the application. The application uses pods to perform the steps of the upgrading. The method includes replacing an old version of the application using an intermediate version of the application, where the intermediate version of the application behaves differently depending on values of definitions in a new supportive column created in the relational database, and replacing the intermediate version of the application with pods using the new version of the application.

Upgrade for relational database dependent application

When a system receives sensitive data, it can request an encryption key from an encryption/decryption unit. A central processing unit (CPU) of the system can encrypt the sensitive data using the encryption key before writing the sensitive data to memory. Thus, the sensitive data is encrypted when written to memory.

Smart data protection

A computer-implemented method for verifying a transaction in a blockchain network may be provided. The blockchain network comprises nodes participating in performing the transaction. The method comprises grouping the nodes of the blockchain network into a plurality of clusters of nodes. For each cluster, the method comprises determining for each node of the cluster performance parameter values, calculating a weighted sum of the determined performance parameter values, designating the node with the highest weighted sum as cluster leader, designating a number of nodes of the cluster whose weighted sum is next to the highest weighted sum, as sub-cluster leader, the number being at least half of the total number of nodes within said cluster, and verifying the transaction for the cluster by the cluster leader and the sub-cluster leaders.

Custom blockchain for IoT devices

A scanner is used to generate a set of processing power consumption metrics for a memory subsystem. From the set of processing power consumption metrics, a number of in-memory computations is determined. From the number of in-memory computations, a total computing score is determined. A user is notified of the total computing score.

Metering computing power in memory subsystems

A computer-implemented method, system and computer program product for applying a unified governance and integration platform to social media data. Data integration definitions for managing and protecting social media data are received. After receiving the data integration definitions for social media data, data integration externalization, governance catalog externalization or lineage externalization may be performed. For example, social media data may be extracted from a database system by a governance and integration unit ('unit') using the data integration definitions. The extracted social media data is then transformed and loaded to the social media data system via a connector linking the data from the unit to the social media data system. In another example, social media data is extracted from the social media data system by the unit, such as via the connector, using the data integration definitions and then transformed and loaded to the database system for analysis.

Applying unified governance and integration platform to social media data

Automatically extracting lineage data for distributed file systems and databases by generating a file folder including data and having a file path, generating a data table associated with the data and the file path, tracking the lineage of data into the file folder and the lineage of data from the data table, and recording an overall lineage comprising the lineage of data into the file folder and from the data table.

Automatically capturing lineage data in distributed systems

Context data pertaining to a target audience to which a product is to be demonstrated can be determined. The target audience can be classified based on the context data. Classifying the target audience can include selecting an audience type out of a predefined plurality of audience types. Customization data can be generated based on the selected audience type. The customization data can be configured to customize demonstration of the product to the target audience.

Generating customization data configured to customize demonstration of a product to a target audience

Applying data owner-defined data protection policies for identity data security within a blockchain environment is provided. A data sharing request for an identity data attribute corresponding to a data owner is received from a data consumer. A data protection policy defined by the data owner that corresponds to the identity data attribute requested by the data consumer is retrieved from a blockchain. The data protection policy is applied to the identity data attribute requested by the data consumer to determine amount of data sharing with the data consumer.

Blockchain network to protect identity data attributes using data owner-defined policies

The present invention generally relates to web applications, and, more particularly, to a distributed virtual control system (VCS) configured to track changes by users to web applications. For this purpose, a system includes a user device configured to access a web server, which includes a web application stored in the web server, wherein the web application is accessible by another user device to make changes to the web application, which changes are stored in a historical collection of versions of the web application in an original repository. The user device is configured to allow the user device to access the historical collection of versions of the web application in the original repository, and to store the changes to the web application made by the other user device in the historical collection of versions of the web application in a first local repository in the user device.

Distributed version control for tracking changes in web applications

A method for detecting software installed on a computer may be provided. The method may comprise obtaining a default user identifier, collecting an installed user identifier, performing an identifier comparison by comparing the installed user identifier with the default user identifier and determining whether an installed user identifier matches a default user identifier, assigning a probability value based on the identifier comparison, performing a threshold comparison of the probability value to the a predetermined threshold value, determining whether the probability value exceeds the threshold value, and in response to determining that the probability value exceeds the threshold value, concluding that the software has been installed on the computer system.

Software detection based on user accounts

Systems, methods, tools and computer programming products for implementing a cognitive data lake that selects or recommends operational database based on historically created data lakes storing files having similar file types, categorizations, metadata, and/or frequency of file usage. Selecting the appropriate operational databases is streamlined by building a knowledge base that is accessible during the creation and/or registration of each data lake. The knowledge base maintains historical records of past data lakes, describing each historical data lake's file types, attributes, metadata, frequency of file usage and at least one operational database implemented to manage the files of the historical data lake. Incoming files streamed or stored by the data lake are analyzed for metadata (extracted from the files as well as separate metadata), categorized based on the metadata, and matched to one or more operational databases of the historical data lakes described by knowledge base, known to manage similar files.

Self-learning operational database management

Systems and methods for managing access to data in a network are provided. In embodiments, a method includes: receiving, by a computer device, a search request regarding data of a participant, the search request including participant parameters associated with the participant; generating, by the computer device, a record of data associated with the participant based on the search request; sending, by the computer device, a request for data to third party nodes of a blockchain system based on the search request and the record; receiving, by the computer device, results from the blockchain system, the results including at least one set of data from a first node of the third party nodes; and determining, by the computer device, that the set of data requires updating based on the results.

Managing access by third parties to data in a network

A method for finding the cause of an error or unexpected behavior of a software application includes providing a list of steps to be executed in order to achieve a certain behavior of the application in a usage scenario and providing a decision tree corresponding with the usage scenario. The decision tree comprises decision nodes that correspond with the steps in the sequence of steps to be executed and leaf nodes indicating one or more possible solutions. The method includes scanning log files to determine whether a step in the list of steps to be executed has not been executed and traversing the decision tree when a step in the list of steps has not been executed. A leaf node of the decision tree that corresponds to a non-executed step is determined and a solution is extracted from the determined leaf node.

System and method for detecting and alerting unexpected behavior of software applications

Approaches presented herein enable restricting access to a locked computing resource in a web browser with a user-tailored CAPTCHA. More specifically, a request for a CAPTCHA is obtained from a web browser of a user attempting to access a resource. A set of terms associated with the user are selected from a pool of terms collected from an environment of the user within a pre-determined time period. A familiarity value of the selected terms indicating a recognizability of the terms by the user is determined. A CAPTCHA of the selected set of terms is generated having a level of graphic noise corresponding to the familiarity value. The generated CAPTCHA is then sent to the web browser. When a response to the CAPTCHA is received from the web browser, it is analyzed to determine whether the response matches the selected set of terms. If so, the web browser is instructed to grant the user access to the resource.

CAPTCHA generation based on environment-specific vocabulary

A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions which are executed by the at least one processor and configure the processor to implement a cognitive security system. The cognitive security system generates a violation array. Each entry of the violation array represents identification of a workflow activity that violates a security policy. Responsive to a new workflow orchestration being created by a user, the cognitive security system compares each activity of the new workflow orchestration to the violation array. Responsive to determining a given activity of the new workflow orchestration exists in the violation array, the cognitive security system recommends to the user to remove the given activity from the new workflow orchestration.

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Cracow, Poland

Krzysztof A Rudek