Abstract: 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.

Abstract: A method, computer system, and a computer program product for text data protection is provided. The present invention may include receiving a text data. The present invention may also include identifying a portion of the received text data having a highest impact on a first confidence score associated with a target model prediction. The present invention may further include generating at least one semantically equivalent text relative to the identified portion of the received text data. The present invention may also include determining that the generated at least one semantically equivalent text produces a second confidence score associated with the target model prediction that is less than the first confidence score associated with the target model prediction. The present invention may further include generating a prompt to suggest modifying the identified portion of the received text data using the generated at least one semantically equivalent text.

Abstract: 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.

Abstract: 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.

Abstract: A method, computer system, and a computer program product for published content protection is provided. The present invention may include receiving a content file from a content management system (CMS). The present invention may include extracting a feature from the received content file. The present invention may include transforming, using an adversarial generation algorithm, the received content file into an adversarial content file. The present invention may include returning the adversarial content file to the CMS. The returned adversarial content file may represent an equivalent of the received content file to a content consumer. The present invention may include preventing an application of the returned adversarial content file in at least one machine learning task based on the adversarial noise included in the returned adversarial content file.

Abstract: A system and method for implementing a marketplace for risk assessed smart contracts issuers and execution providers in blockchains in a computer environment are presented. A smart contract, issued by one or more blockchain nodes to a secondary blockchain and accepted by a primary blockchain, may be executed following a risk assessment to recursive call attack vulnerabilities of the smart contract according to a reputation of both the one or more blockchain nodes and the one or more execution nodes.

Abstract: Various embodiments are provided for automated evaluation of machine learning models in a computing environment by one or more processors in a computing system. A level of robustness of a machine learning model against adversarial whitebox operations may be evaluated and determined by applying a data set used for testing the machine learning model, one or more adversarial operation objectives, an adversarial threat model, and a selected number of hyperparameters. Results from the adversarial operation may be analyzed and a modified machine learning model may be generated while performing the evaluating and determining.

Abstract: Embodiments are provided for intelligent augmentation of word representations in a computing system by a processor. One or more character shape embeddings may be created in an artificial neural network (ANN) by augmenting one or more word representations based on a set of natural language processing (NLP) data, a set of word embedding vectors, and one or more clustering operations. A shape, a category, and a contextual identify of the one or more word representations may be analyzed used in creating the one or more character shape embeddings.

Abstract: 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.

Abstract: A system and method for reducing risk of smart contracts in blockchains in a computer environment are presented. One or more smart contracts may be accepted or rejected from a secondary blockchain to a primary blockchain according to a risk assessment to recursive call attack vulnerabilities.

Abstract: Embodiments are provided for intelligent augmentation of word representations in a computing system by a processor. One or more character shape embeddings may be created in an artificial neural network (ANN) by augmenting one or more word representations based on a set of natural language processing (NLP) data, a set of word embedding vectors, and one or more clustering operations. A shape, a category, and a contextual identify of the one or more word representations may be analyzed used in creating the one or more character shape embeddings.

Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.

Abstract: A system and method for implementing a marketplace for risk assessed smart contracts issuers and execution providers in blockchains in a computer environment are presented. A smart contract, issued by one or more blockchain nodes to a secondary blockchain and accepted by a primary blockchain, may be executed following a risk assessment to recursive call attack vulnerabilities of the smart contract according to a reputation of both the one or more blockchain nodes and the one or more execution nodes.

Abstract: A system and method for reducing risk of smart contracts in blockchains in a computer environment are presented. One or more smart contracts may be accepted or rejected from a secondary blockchain to a primary blockchain according to a risk assessment to recursive call attack vulnerabilities.

Abstract: Various embodiments are provided for providing intelligent data security in a computing environment are provided. One or more data vulnerabilities may be identified from a plurality of data. Selected data having the one or more identified data vulnerabilities may be protected by applying one or more data protection policies or rules, wherein the selected data is de-identified.

Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.

Abstract: 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.

Abstract: Various embodiments are provided for managing regulatory compliance for an entity in a computing environment by a processor. A law, policy, regulation, or a combination thereof extracted from one or more segments of text data from one or more data sources may be identified requiring an obligation to be performed by the entity.

Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.

Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.