International Business Machines Corporation

Stefano Braghin

Spyridon Antonatos

Killian Levacher

Aris Gkoulalas-Divanis

Naoise Holohan

Marco Simioni

Emanuele Ragnoli

Ioannis Gkoufas

Olivier Verscheure

Rahul Nair

Michael Wurst

Ngoc Minh Tran

Srikumar Venugopal

Vasileios Vasileiadis

Pol MacAonghusa

Gokhan Sagirlar

Sameep Mehta

Elizabeth Daly

Mathieu Sinn

Akshar Kaul

Manish Kesarwani

Martin Stephenson

Michele Berlingerio

Paulito Pedregosa Palmes

Christian Pinto

Michael Johnston

Vincent Petrus Anthonius Lonij

Yiannis Gkoufas

Pol Mac Aonghusa

Pranay Anchuri

Rana E Novack

Adi Ionel Botea

Akihiro Kishimoto

Marco Luca Sbodio

Ambrish Rawat

Derek Wayne Botti

Andrea Reale

Michele Gazzetti

Konstantinos Katrinis

John Sheehan

Valentina Rho

Giulio Zizzo

Cennet Oguz

Alessandro Pomponio

In an approach for storage, search, acquisition, and composition of a digital artifact, a processor obtains the digital artifact in a digital marketplace platform. The digital artifact is a collection of digital data with automatically generated and verifiable provenance and usage data. A processor transforms the digital artifact to define an access privilege. A processor shares the digital artifact in the digital marketplace platform by providing a view of a catalogue including the digital artifact. A processor authorizes a usage request based on the access privilege. A processor rewards a source of the digital artifact based on the usage of the digital artifact.

Digital artifact marketplace

A method, computer program, and computer system are provided for predicting and assessing risks on websites. Data corresponding to historical interactions of a user with one or more websites is accessed. A simulation of actions of the user is generated based on the accessed data, and actions of the user are simulated on a pre-defined target website based on the generated simulation of the actions of the user. Risks on the target website are identified based on simulating the actions of the user. The website is updated to mitigate the identified risks.

Federated generative models for website assessment

A method, computer system, and a computer program product are provided for query management optimization in a distributed data management system. In one embodiment, at least one query is received. The query is then analyzed and related information associated with the query is obtained. When information exists in a database relating to previously executed queries similar to the received query, that information is obtained. A query execution plan is then formulated using any existing information and information relating to the similarly previously executed queries.

Database query optimization based on analytics

Disclosed are techniques for linking information about individual entities across multiple datasets. A target dataset with some information corresponding to at least one attribute of an entity is received. Semantic processing is performed on the target dataset to extract semantic representations of the information and corresponding attributes, which is utilized to search at least one other dataset for additional information that is absent from the target dataset, corresponding to at least one attribute of the entity, which are used to augment the target dataset with additional information corresponding to the entity. This is repeated iteratively, with each subsequent iteration including semantic representations of information found in the searches of previous iterations until no additional information about the entity is found when searching the multiple datasets with semantic representations of the now augmented target dataset. In some embodiments the augmented target dataset is used for determining privacy risks for the entity.

Augmented privacy datasets using semantic based data linking

In an approach for transforming workflows based on goals and constraints, a processor receives a workflow definition and one or more events for a workflow output by a workflow orchestrator, wherein the one or more events are at least one of a parsing event and a scheduling event. A processor determines, using one or more transformers, one or more transformations to the workflow based on a set of goals and constraints, wherein the one or more transformations is at least one of addition of a new node, addition of a new graph, modification of at least one existing node, modification of at least one existing graph, removal of at least one existing node, and removal of at least one existing graph. A processor dynamically applies, using one or more enforcers, the one or more transformations to the workflow based on the set of goals and constraints.

Workflow transformation framework

One or more computer processors transmit a machine learning model and an associated loss function to a worker, wherein the worker isolates private data. The one or more computer processors receive a plurality of encrypted gradients computed utilizing the transmitted machine learning model, the associated loss function, and the isolated private data. The one or more computer processors generate a plurality of adversarial perturbations, wherein the plurality of adversarial perturbations includes true perturbations and false perturbations. The one or more computer processors obfuscate the generated plurality of adversarial perturbations. The one or more computer processors transmit the obfuscated adversarial perturbations to the worker. The one or more computer processors harden the machine learning model utilizing the transmitted obfuscated adversarial perturbations and the private data.

Federated private adversarial training

A first copy of a heterogeneous program payload is provided to a first computing device. The heterogeneous program payload contains an unencrypted component and a set of one or more encrypted components. The set of encrypted components corresponding to a set of one or more programs. The unencrypted component of the heterogeneous program payload includes loader program code configured to receive a first license key. The loader program code is configured to, in response to receiving the first license key, perform a decryption action against the set of encrypted components of the heterogeneous program payload.

Software access through heterogeneous encryption

Systems and techniques that facilitate policy-driven views of datasets are provided. In various embodiments, a system can comprise a data component that can access a dataset. In various instances, the system can further comprise a view policy component that can respectively correlate a set of security credentials to a set of view instructions associated with the dataset. In various embodiments, the system can further comprise an input component that can receive as input a first security credential that is listed in the set of security credentials. In various aspects, the system can further comprise an output component that can identify a first view instruction that is listed in the set of view instructions associated with the dataset, wherein the first view instruction is respectively correlated to the first security credential. In various cases, the output component can generate as output a view of the dataset based on the first view instruction.

Policy-driven views of datasets

Embodiments for ensemble training in a distributed marketplace in a computing environment. One or more ensemble machine learning models may be provided from a plurality of machine learning models competing within the distributed marketplace that achieve a performance on ensemble training data equal to or greater than a selected performance threshold, wherein the distributed marketplace is a blockchain.

Ensemble training in a distributed marketplace

Embodiments of the invention are directed to techniques that include receiving a query intended for a targeted database and determining that the query is from an unauthorized user. A response is returned to the unauthorized user generated by a model, the response being dynamically generated to fulfill the query. The model is configured to generate responses consistent with any previous responses returned to the unauthorized user.

Defense of targeted database attacks through dynamic honeypot database response generation

Disclosed are techniques for determining data relationships between privacy-restricted datapoints, sourced over a computer network, which require data privacy measures concealing at least some datapoints from other clients in the network that the datapoint respectively do not originate from. A first client encrypts a first datapoint with a public key of a public/private encryption scheme and communicates it to the second client along with the public key. The second client encrypts a corresponding second datapoint with the public key, then determines a relationship between the two encrypted datapoints, and communicates the determined relationship to a central client along with the public key. Random noise is encrypted by the central client and added to the determined relationship, then sent together to the first client, followed by decryption by the first client using the private key. The central client extracts the random noise after receiving the decrypted determined relationship.

Preserving inter-party data privacy in global data relationships

Systems, computer-implemented methods, and computer program products that can facilitate sensitive data policy recommendation are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can employ an artificial intelligence model to extract compliance data from a data source. The computer executable components can further comprise a recommendation component that can recommend a sensitive data policy based on the compliance data. In some embodiments, the recommendation component can further identify one or more sensitive data entities of a sensitive data dataset that are affected by actionable obligation data of the data source.

Sensitive data policy recommendation based on compliance obligations of a data source

Embodiments of the present invention provide computer-implemented methods, computer program products, and systems. Embodiments of the present invention can be used to receive position information for one or more user devices and location information for an area. Embodiments of the present invention can predict one or more locations of the one or more user devices. Embodiments of the present invention can, in response to a request for navigation services, dynamically navigate a first user device of the one or more devices to a second user device of the one or more devices within the area.

Collaborative positioning navigation

Embodiments for providing intelligent data replication and distribution in a computing environment. Data access patterns of one or more queries issued to a plurality of data partitions may be forecasted. Data may be dynamically distributed and replicated to one or more existing data partitions or additional of the plurality of data partitions according to the forecasting.

Intelligent data distribution and replication using observed data access patterns

Embodiments include a method for one or more processors to receive an organic dataset and a domain knowledge base. The one or more processors identify private data entities present within the organic dataset. The one or more processors determine statistical properties of the private data entities identified within the organic dataset. The one or more processors create a plurality of test data templates by removing the private data entities from the organic dataset. The one or more processors select from the domain knowledge base, synthetic data entities that match a data type of the removed private data entities, respectively, and align with the statistical properties of the private data entities, and the one or more processors generate synthetic test data by inserting, respectively, the synthetic data entities of the matching data type for the removed private data entities in the test data templates.

Synthetic deidentified test data

Growing community of inventors

Dublin, Ireland

Stefano Braghin