Abstract: An example operation may include one or more of receiving a blockchain request comprising a timestamp added by one or more endorsing nodes included within a blockchain network, identifying that the timestamp added by an endorsing node from among the one or more endorsing nodes is a modification to a previously added timestamp provided by the computing node, determining a reputation value for the endorsing node based on a difference between the timestamp added by the endorsing node and the previously added timestamp provided by the computing node, and transmitting the determined reputation value of the endorsing node to an ordering node within the blockchain network.

Abstract: A computer-implemented method is provided for estimating output confidence of a black box Application Programming Interface (API). The method includes generating paraphrases for an input text. The method further includes calculating a distance between the input text and each respective one of the paraphrases. The method also includes sorting the paraphrases in ascending order of the distance. The method additionally includes selecting a top predetermined number of the paraphrases. The method further includes inputting the input text and the selected paraphrases into the API to obtain an output confidence score for each of the input text and the selected paraphrases. The method also includes estimating, by a hardware processor, the output confidence of the input text from a robustness of output scores of the input text and the selected paraphrases.

Abstract: A computer-implemented method is provided for estimating output confidence of a black box Application Programming Interface (API). The method includes generating paraphrases for an input text. The method further includes calculating a distance between the input text and each respective one of the paraphrases. The method also includes sorting the paraphrases in ascending order of the distance. The method additionally includes selecting a top predetermined number of the paraphrases. The method further includes inputting the input text and the selected paraphrases into the API to obtain an output confidence score for each of the input text and the selected paraphrases. The method also includes estimating, by a hardware processor, the output confidence of the input text from a robustness of output scores of the input text and the selected paraphrases.

Abstract: Computer hardware and/or software that performs the following operations: (i) identifying a test input for a system under test, the system under test configured to determine a strength of a relationship between received inputs; (ii) determining, from a data store of potential inputs, a set of inputs for which the strength of the relationship to the identified test input according to the system under test meets a first threshold; and (iii) utilizing the determined set of inputs to test a transitive consistency of an output of the system under test.

Abstract: A computer implemented method of hypothesis scoring based on causal relationships is provided. The computer implemented method includes creating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses, and obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function. The computer implemented method further includes assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model, and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms to test the propagating scores for reasonableness. The computer implemented method further includes determining a final pro and con score for the root hypothesis, and presenting the final pro and con scores representing a prediction of the hypotheses to a user.

Abstract: An example operation may include one or more of identifying a digital token issued via a blockchain, determining an asset that is linked to the digital token, a current custodian of the asset that is linked to the digital token, and a risk value associated with the asset based on attributes of the asset, generating a graph that comprises a path between a user that owns the digital token and the current custodian of the asset, embedding the graph within a field of a template and embedding the risk value within a second field of the template to generate a filled-in template, and displaying the filled-in template within a user interface.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A method is provided for determining support of a hypothesis by opinion sentences. The method converts sentence structures in the opinion sentences using various sentence structure conversion methods to obtain converted opinion sentences. For each converted opinion sentence, the method calculates a difference between a proximity label value indicating proximity to the hypothesis and an intermediate score before and after a conversion, adopts the conversion responsive to a condition being met relative to the difference, and adopts the opinion sentence instead responsive to the condition being unmet. The method creates sub-opinions using the various methods applied to adopted conversions and opinion sentences, and obtains an intermediate score for each sub-opinion.

Abstract: An example operation may include one or more of receiving a resource request from a client, identifying a unique chaincode identifier associated with the resource request, re-instantiating a version of chaincode based on the unique chaincode identifier, the re-instantiation configured to disregard any subsequently implemented versions of the chaincode at the computing node, executing the resource request based on the re-instantiated version of the chaincode to generate a result, and transmitting the result to the client.

Abstract: An example operation may include one or more of receiving a resource request from a client, identifying a unique chaincode identifier associated with the resource request, re-instantiating a version of chaincode based on the unique chaincode identifier, the re-instantiation configured to disregard any subsequently implemented versions of the chaincode at the computing node, executing the resource request based on the re-instantiated version of the chaincode to generate a result, and transmitting the result to the client.

Abstract: Smart contract code is verified by storing smart contract code, identifying a type system for verifying a determinism of the smart contract code based on a first set of security-level values and a second set of security level values, and verifying the determinism of the smart contract code by taking the first set of security-level values as deterministic values and the second set of security level values as non-deterministic values.

Abstract: A method is provided for validating a hypothesis sentence. The method extracts, from a document database D using a hypothesis sentence that includes a causal part and a consequence part, a set D1 of documents related to the causal part. The method extracts, from set D1, a set S of sentences that include expressions of opinion. The method obtains a word list W of words that have a high co-occurrence in the set D1. The method selects, from the set S, a set S1 of sentences that are positionally close to any of the words in the word list W. The method selects, from the set S, a set S2 of sentences that are related to the words in the consequence part of the hypothesis. The method extracts and displays sentences included in both the set S1 and the set S2 as opinion sentences in relation to the hypothesis sentence.

Abstract: An example operation may include one or more of receiving a uniform resource indicator (URI) of a blockchain peer node that has access to a blockchain distributed among a plurality of blockchain peer nodes, identifying blockchain channel identification information which identifies a unique channel name associated with the blockchain, generating a blockchain-based URI that includes an identification of the URI of the blockchain peer node and the channel name associated with the blockchain, and storing the generated blockchain-based URI on a distributed ledger.

Abstract: A processor may assign a bridging blockchain client. The bridging blockchain client may link a first system to a second system. The first and second systems may be on one or more blockchains. The processor may identify that an exchange has been initiated. The processor may generate one or more assets in response to the exchange. The processor may process the exchange. The processing of the exchange may include the bridging blockchain client accepting a probability of failure of the exchange.

Abstract: An example operation may include one or more of receiving a uniform resource indicator (URI) of a blockchain peer node that has access to a blockchain distributed among a plurality of blockchain peer nodes, identifying blockchain channel identification information which identifies a unique channel name associated with the blockchain, generating a blockchain-based URI that includes an identification of the URI of the blockchain peer node and the channel name associated with the blockchain, and storing the generated blockchain-based URI on a distributed ledger.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A computer-implemented method is provided for estimating output confidence of a black box Application Programming Interface (API). The method includes generating paraphrases for an input text. The method further includes calculating a distance between the input text and each respective one of the paraphrases. The method also includes sorting the paraphrases in ascending order of the distance. The method additionally includes selecting a top predetermined number of the paraphrases. The method further includes inputting the input text and the selected paraphrases into the API to obtain an output confidence score for each of the input text and the selected paraphrases. The method also includes estimating, by a hardware processor, the output confidence of the input text from a robustness of output scores of the input text and the selected paraphrases.

Abstract: A method is provided for determining support of a hypothesis by opinion sentences. The method converts sentence structures in the opinion sentences using various sentence structure conversion methods to obtain converted opinion sentences. For each converted opinion sentence, the method calculates a difference between a proximity label value indicating proximity to the hypothesis and an intermediate score before and after a conversion, adopts the conversion responsive to a condition being met relative to the difference, and adopts the opinion sentence instead responsive to the condition being unmet. The method creates sub-opinions using the various methods applied to adopted conversions and opinion sentences, and obtains an intermediate score for each sub-opinion.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A method is provided for validating a hypothesis sentence. The method extracts, from a document database D using a hypothesis sentence that includes a causal part and a consequence part, a set D1 of documents related to the causal part. The method extracts, from set D1, a set S of sentences that include expressions of opinion. The method obtains a word list W of words that have a high co-occurrence in the set D1. The method selects, from the set S, a set S1 of sentences that are positionally close to any of the words in the word list W. The method selects, from the set S, a set S2 of sentences that are related to the words in the consequence part of the hypothesis. The method extracts and displays sentences included in both the set S1 and the set S2 as opinion sentences in relation to the hypothesis sentence.