International Business Machines Corporation

Institute for Information Technology Advancement

Danny Soroker

Chandrasekhar Narayanaswami

Lisa M Frankel

Justin David Weisz

Herbert Scott McFaddin

Francois Huaulme

Ashish Kundu

Amit Anil Nanavati

Guruduth Somasekhara Banavar

Daniel Mark Coffman

Clifford A Pickover

Peter Kenneth Malkin

Jonathan Hudson Connell, Ii

Robert G Farrell

Jacquelyn Annette Martino

Jonathan Paul Munson

Lawrence David Bergman

Maryam Ashoori

Michael S Karasick

Jason Benjamin Ellis

James Arthur Lindeman

Yichong Yu

Jingtao Wang

Netta M Shani

Young Sang Paik

Sean Lee

Yi-Min Chee

Sharon Mary Trewin

Ramon Caceres

Kouichi Ono

Masahiro Hori

Marcel-Catalin Rosu

Apratim Purakayastha

Juan Manuel Huerta

Richard J Cardone

Samuel Monk Weber

John Joseph Barton

Paul Robert Carini

David Joseph Streeter

Robert M Fuhrer

Daniel Irimie Dig

Sébastien Demathieu

Chandrasekar Narayanaswami

An example operation may include one or more of generating, by an organization node, an item traceability graph comprising a plurality of expandable nodes, and executing, by the organization node, a smart contract to: acquire user role-based behavior results from the blockchain, and adjust expandability settings of the plurality of the expandable nodes based on the user role-based behavior results.

Behavior driven graph expansion

An example operation may include one or more of acquiring, by an organization node, a user profile from a blockchain, determining, by the organization node, a role of the user based on the user profile, detecting, by the organization node, user actions directed to graph expansions, and executing, by the organization node, a smart contract to analyze user behavior based on the detected user actions and the role to produce role-based user behavior parameters.

An example operation may include one or more of authenticating a user, by a first system node, based on a first set of user credentials, computing, by the first system node, a second set of user credentials for a second system node, testing the second system node, by the first system node, to determine if the second system node has a user with the second set of the user credentials, and responsive to the second system node not having the user with the second set of the user credentials, creating a user with the second set of the user credentials.

Dynamic management of user identifications

An example operation may include one or more of authenticating a user, by a first system node, based on a first set of user credentials, computing, by the first system node, a second set of user credentials for a second system node, determining, by the first system node, if the second system node has a user with the second set of the user credentials, and responsive to the second system node not having the user with second set of the user credentials, deleting, by the first system node, an existing user of the second system node.

An example operation may include one or more of registering a first service node and a second service node for accessing a common data store, providing to the second client node, by the first client node, a data access request token key and a data access receipt key corresponding to a data access request, responsive to a receipt of the access request token key and the data access receipt key by the second service, retrieving a result from the common data store; and providing the result to the second client node.

Decentralized secure data sharing

An example operation may include one or more of authenticating, by a first service node, to a first client node, receiving, by the first service node, a data access request from the first client node, comprising request parameters and a request token, generating, by the first service node, a receipt key corresponding to the data access request, and sharing data with a second client node based on the request token and the receipt key.

An example operation may include one or more of registering, by a data sharing node, a first service node and a second service node for accessing a common data store, causing, by the data sharing node, a first client node associated with the first service node to provide a data access request token key and a receipt key to a second client node associated with the second service node based on a data access request received from the second client node, assigning, by the data sharing node, weights to the data access request token key and to the receipt key, and causing, by the data sharing node, the second service node to retrieve a result from the data source based on the assigned weights.

A display adaption method, system, and computer program product include determining an obscured area of an interface of a screen that is obscured by a user, learning a pattern of the obscured area of the screen that is obscured over a time frame, and adapting the interface of the screen to change the interface of the screen to change an interference by the user with the interface of the screen such that the obscured area is reduced.

Adapting a display of interface elements on a touch-based device to improve visibility

Provided is a computer-implemented method for automatically preserving privacy in a user interface. The method includes detecting privacy objects that are being presented via a UI of a computing device to a first user. A security status of the UI is evaluated based at least in part on analyzing audio captured by an audio capture device of the computing device. A privacy mode of the UI that executes privacy actions that are associated with the detected privacy objects is activated based on determining that the security status is in an unsecure state. The privacy mode is deactivated based on determining that the security status has changed from the unsecure state to a secure state, in which determining that the security status has changed from unsecure to secure is based on analyzing the audio captured by the audio capture device of the computing device.

Cognitive widgets and UI components for preserving privacy and security

Embodiments are directed to a system for implementing a restricted-operation region. The system includes an instruction development module configured to be utilized in the development of a set of instructions that implement an operation policy of the restricted-operation region. The set of instructions is configured to, when interpreted, implement the operation policy by controlling at least one function of a vehicle that attempts to operate within the restricted-operation region. The system further includes a first transmitter configured to transmit the set of instructions to the vehicle, wherein a processor of the vehicle is configured to interpret the set of instructions based at least in part on a determination that the vehicle is attempting to operate within the restricted-operation region.

Implementing a restricted-operation region for unmanned vehicles

Crypto-glasses include systems that implement a method of authentication of users by blinking, the crypto-glasses including a frame configured so as to be worn by a user, a processor, a display device communicating with the processor so as to dynamically display data, and a communication unit, as executed by the processor, to execute the method of authentication by transmitting data to the display device for performing the authentication of the user to interact with the display device. The communication unit is configured to display in an optical unit of the crypto-glasses a key map which correlates data input into the display device with keys of the display device, the key map indicating data different from that of the keys of the display device.

Method and system for securing the entry of data to a device

A system and computer product for validating the consistency between quantitative and natural language textual evaluations. An example method involves computing a numeric score for a textual evaluation, comparing the numeric score to a quantitative evaluation, and producing a rating based on the similarity of the two evaluations.

System support for evaluation consistency

A program code execution is monitored. Variable type and value information the one or more variables in the program code take during the execution of the program code are stored, and compiled over multiple execution of the program code as historical run-time execution traces. A code editor user interface may present the historical run-time execution traces for inspection, whether or not the program code is currently executing. Statistical properties associated with the variable type and value information may be computed. Future variable type and value the one or more variables might take during future execution of the program code may be predicted.

Capture and display of historical run-time execution traces in a code editor

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Larchmont, NY, United States of America

Danny Soroker