International Business Machines Corporation

Kyndryl, Inc.

Venkatraman Ramakrishna

Sougata Mukherjea

Apurva Kumar

Kuntal Dey

Praveen Jayachandran

Petr Novotny

Palanivel Andiappan Kodeswaran

Dushyant K Behl

Nitin Gaur

Yu Chin Fabian Lim

Krishnasuri Narayanam

Vinayaka D Pandit

Angelo De Caro

Sayandeep Sen

Chander Govindarajan

Chun Hui Suen

Nitendra Rajput

Yohei Ueda

Dhinakaran Vinayagamurthy

Alwyn R Lobo

Prasad G Naldurg

Luba Cherbakov

Meghna Singh

Bishakh Chandra Ghosh

Donna N Dillenberger

Amith Singhee

Timothy S Olson

Vikas Agarwal

Qi Zhang

Emanuele Ragnoli

Pralhad Dinesh Deshpande

Arvind Seshadri

Sandeep Nishad

Ashok Pon Kumar Sree Prakash

Takuya Nakaike

Moriyoshi Ohara

Sumit Mittal

Michael Steiner

Ermyas Abebe

Tatsushi Inagaki

Shiqiang Wang

Vishal Singh Batra

Senthilnathan Natarajan

Timothy Olson

Dileban Karunamoorthy

Saurabh Srivastava

Zhou Yinsheng

Prashant Sachan

Yining Hu

A system and method for a multi-party computation (MPC) is provided. In implementations, a method includes identifying a blockchain network and a computing device to perform an MPC based on an index; generating an MPC request including a function to be performed by the blockchain network and the computing device, data required for the function, and a verification policy defining a verification protocol to be performed by the blockchain network and the computing device; sending the MPC request to the blockchain network and the computing device; and receiving responses from a representative computing node of the blockchain network and the computing device, wherein each of the responses includes: an output of an MPC protocol performed by the blockchain network and the computing device to jointly compute the function while keeping the inputs private from one another and private from the computing system; and a proof based on the verification policy.

Collaborative computation across blockchain networks

A computer-implemented method for automatically and digitally securing an asset is disclosed. The computer-implemented method includes hashing a secret preimage to produce a secret hash. The computer-implemented method further includes locking a digital collateral asset with the secret hash for a first predetermined period of time. The computer-implemented method further includes locking a digital loan asset with the secret hash for a second predetermined period of time, wherein the second predetermined period of time is less than the first predetermined period of time. The computer-implemented method further pledging a digital loan repayment up to the amount of time of the first predetermined period of time plus the second predetermined period of time. The computer-implemented method further includes responsive to receiving a pledge for the digital loan repayment, automatically unlocking the digital collateral asset for a borrower of the digital loan asset.

Method for digitally securing an asset

A group of transactions to be rolled back in a blockchain ledger can be identified. Whether the transactions in the group are eligible to be rolled back together can be determined. Other transactions can be recommended, and the other transactions may be added to the group to be rolled back together. A rollback transaction can be added to the blockchain ledger that rolls back effect of the transactions, where the rollback transaction has zero or more inputs and zero or more output, the rollback transaction having at least one selected from at least one input and at least one output. An unspent output of a transaction in the group is provided as an input of the rollback transaction. Input of a transaction in the group, that is not an output of another transaction in the group, is provided as an output of the rollback transaction.

Blockchain ledger rollback

An example operation may include one or more of receiving a request for storage at a blockchain network, attaching, via a blockchain node, a verifiable credential created by a self-sovereign identity (SSI) network to a blockchain transaction associated with the request, where the verifiable credential includes a claim of the blockchain node and a proof of the SSI network that created the verifiable credential, transmitting the blockchain transaction and the attached verifiable credential to one or more other blockchain nodes, and storing the blockchain transaction and the attached verifiable credential via a data block on the blockchain.

Blockchain network identity management using SSI

An example operation may include one or more of receiving a data block from a blockchain node, determining a current transaction state of each of a plurality of endorser nodes based on transaction history stored within read and write sets of the data block, determining a current load of each of the plurality of endorser nodes based on performance data stored within the data block, and outputting information about the current transaction state and the current load of each of the plurality of endorser nodes via a user interface.

Optimal endorser node determination based on state

An example operation may include one or more of retrieving decentralized identifiers (DIDs) of a plurality of blockchain peers included within a blockchain network, generating a blockchain declarative descriptor (BDD) which uniquely identifies the blockchain network, where the BDD comprises a machine-readable data file with a first field includes the retrieved DIDs of the blockchain network, a second field including signature data of the plurality of blockchain peers, and a third field including metadata, and transmitting the generated BDD to a blockchain network registry.

Blockchain declarative descriptor for cross-network communication

Methods and arrangements for effecting authentication in a secure transaction. There are defined, on behalf of a user, individuals who are members of a social network of the user. There is received, from the user, a transaction request for a secure transaction. An authentication test is conducted with the user and, upon meeting a predetermined requirement of the authentication test, the transaction request is validated. The authentication test requests the user to confirm at least one information item related to at least one member of the user's social network. Other variants and embodiments are broadly contemplated herein.

Usable security with social network assistance

An example operation may include one or more of collecting, by a lead peer, state and quality of service (QoS) data from a plurality of peers of a blockchain network, building, by the lead peer, a network graph (NG) based on the state and the QoS data from the plurality of the peers, and mapping, by the lead peer, the NG to a block deliver graph (BDG), wherein edges of the BDG represent a sequence of blocks to be sent from a source peer to a destination peer.

Optimization of delivery of blocks

An approach is provided for detecting and analyzing an anomaly in application performance in a client-server connection via a network. A status code of a response sent by a server to a client, a round trip latency time (RTT) of the response, and a time out of a connection between client and server are determined. Using a k-means clustering algorithm, buckets of RTT values clustered into lower and higher values, and running counts and means for the RTT values in each bucket, an RTT value is determined to exceed a threshold value. Based on the status code, the RTT value exceeding the threshold, and the connection time out, the anomaly is detected. Based on temporal and textual analyses of log entries and an environment analysis, candidate root causes of a failure that resulted in the anomaly are determined.

Detecting and analyzing performance anomalies of client-server based applications

One embodiment provides a computer implemented method, including: receiving an application to be deployed on a container-based environment; obtaining a specification for the application including information regarding a portion of the application contained within a given container; extracting portion information corresponding to connections between different portions of the application and interferences between different portions of the application; identifying affinity indicators and anti-affinity indicators for the portions of the application, wherein the affinity indicators are based upon the connections between different portions of the application and wherein the anti-affinity indicators are based upon the interferences between different portions of the application; and constructing affinity rules and anti-affinity rules for the containers by combining the affinity indicators to construct affinity rules and combining the anti-affinity indicators to construct anti-affinity rules.

Automatic generation of affinity and anti-affinity rules

An example operation may include one or more of receiving a request to merge a first blockchain network and a second blockchain network, the request comprising a script that specifies a network structure, synthesizing the script with configuration data of the first and second blockchain networks to generate a plurality of merge operations, and merging the first blockchain network with the second blockchain network based on the plurality of merge operations to create a merged blockchain network, wherein the merging comprises merging chaincodes and channels from the first and second blockchain networks into merged chaincodes and merged channels.

Automated merge of DLT networks

An example operation may include one or more of identifying a registered interest associated with a requestor on a blockchain, accessing a smart contract stored on the blockchain, determining a match between the registered interest and blockchain transaction information, determining the requestor associated with the registered interest has access permissions to access the blockchain transaction information based on access control rules, and creating a temporary bilateral smart contract including the requestor, and an owner of the blockchain transaction information, and the temporary bilateral smart contract provides permission for the requester to access the blockchain transaction information.

Private resource discovery and subgroup formation on a blockchain

An example operation may include one or more of creating, via chaincode, a link between a non-participant system and a data field stored on a private blockchain, where the data field comprises participant data of the private blockchain, detecting a change in a value of the participant data based on a read operation from the data field stored on the private blockchain, generating a notification of the changed value of the participant data, and transmitting the notification to the non-participant system based on the link between the non-participant system and the data field.

Off-chain notification of updates from a private blockchain

An example operation includes one or more of connecting, by an identity provisioning node, a blockchain one to a blockchain two, creating, by an identity provisioning node, an interoperation identity network (IIN) for the blockchain one and for the blockchain two as an instance of a self-sovereign identity (SSI) network, executing a smart contract to: invoke an IIN access control policy, map attributes and permissions of the blockchain one to attributes and permissions of the blockchain two based on the IIN access control policy, and generate a valid verifiable credential (VC) of the IIN in the blockchain one and in the blockchain two based on the mapped attributes and the permissions.

Cross-network identity provisioning

A blockchain configuration may be used to store smart contracts. One example method of operation may include one or more of identifying a metric configuration associated with a smart contract stored in a blockchain, logging an event which is part of the metric configuration, determining whether the event supports requirements of the smart contract, determining whether a smart contract policy in the smart contract matches a system policy, and updating the smart contract on the blockchain when the requirements of the smart contract are supported by the event and the smart contract policy matches the system policy.

Smart contract admission check and fault tolerance in a blockchain

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Bengaluru, India

Venkatraman Ramakrishna