International Business Machines Corporation

Green Market Square Limited

Sachiko Yoshihama

Kohichi Kamijoh

Takaaki Tateishi

Futoshi Iwama

Shunichi Amano

Hiroaki Nakamura

Seiji Munetoh

Yohei Ueda

Tatsushi Inagaki

Issei Yoshida

Hiroshi Maruyama

Miki Ishikawa

Shoko Suzuki

Yohei Ikawa

Masayoshi Teraguchi

Shohei Hido

Naohiko Uramoto

Takuya Mishina

Karim Hamzaoui

Yu Zhang

Marco Pistoia

Peter Kenneth Malkin

Shin Saito

Adi Sharabani

Lin Luo

Anthony Tom Levas

Ory Segal

Mark Edward Podlaseck

Guy Podjarny

Jennifer Ceil Lai

Kohtaroh Miyamoto

Shun Xiang Yang

Yasuharu Katsuno

Shinya Kawanaka

Ken Mizuno

Rikiya Takahashi

Timothy David Ebringer

Frederik De Keukelaere

Tim Ebringer

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.

Blockchain notification board storing blockchain resources

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.

Estimating output confidence for black-box API

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.

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.

Blockchain timestamp agreement

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.

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. The method represents an amount of support for the hypothesis by obtaining and displaying a final score for each adopted conversions and opinion sentences based on the intermediate scores for the sub-opinions and for adopted conversions and opinion sentences.

Optimized document score system using sentence structure analysis function

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.

Static analysis of smart contract determinism

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.

Extracting important sentences from documents to answer hypothesis that include causes and consequences

An example operation may include one or more of receiving a unique identifier of a blockchain system resource from among a plurality of blockchain system resources associated with a blockchain, generating a notification board for the blockchain which is implemented independently from the blockchain and stored on a distributed ledger including the blockchain, and storing the unique identifier of the blockchain resource and a blockchain ID within the notification board on the distributed ledger.

An example operation may include one or more of receiving a blockchain request from a client application in a blockchain network, receiving validity information of a timestamp included in the blockchain request from one or more endorsing nodes in the blockchain network, modifying the timestamp included in the blockchain request based on the validity information received from the one or more endorsing nodes, ordering the blockchain request among a group of blockchain requests based on the modified timestamp with respect to timestamps of other blockchain requests in the group, and storing the ordered group of blockchain requests within a data block among a hash-linked chain of data blocks.

A mechanism is provided to improve the availability of an ICS and an external system that uses data from the ICS by ensuring operation of the ICS and operation of the system even if an anomaly has occurred in a device in the ICS. The mechanism receives measured data from the plurality of devices, calculates prediction data by using the measured data and correlation information used for deriving prediction data for correlated devices, and provides the measured data and the prediction data.

Increasing availability of an industrial control system

Growing community of inventors

Kawasaki, Japan

Sachiko Yoshihama