International Business Machines Corporation

Kyndryl, Inc.

Edgar Adolfo Zamora Duran

Rick A Hamilton, Ii

Luis Carlos Cruz Huertas

Franz Friedrich Liebinger Portela

Roxana Monge Nunez

Gregory J Boss

Cesar Augusto Rodriguez Bravo

Ninad D Sathaye

Clifford A Pickover

Sarbajit Kumar Rakshit

Mary Swift

John Richard Feezell

Esteban Arias Navarro

Shikhar Kwatra

Komminist S Weldemariam

Charles Evan Beller

Franz F Liebinger

Jose Cano Zapata

Juan G Rodriguez

Luis A Mena Monge

Jose P Monge Bolanos

Craig M Trim

Jeronimo Irazabal

Christopher L Molloy

Bernadette Ann Pierson

Jayashree Vaidyanathan

Juan Gabriel Rodriguez Arguedas

Yanil Zeledon

Effron Esseiva

James R Kozloski

Maja Vukovic

Wayne Francis Tackabury

Ryan G Dejana

Ricardo Golcher Ugalde

Desilda Toska

Blanca R Navarro Piedra

Wouter Denayer

Maria Esmeralda Hasbun Pacheco

Juan G Rodriquez Arguedas

Barun Das

Joseph M Phillips, Jr

Sheyla V Vargas

Carlos Gustavo Alfaro Briceno

Hari K Narasimhamurthy

Juan G Rodriguez Arguedas

Ivonne R Cuervo

Radha Radha Mohan De

Andrea Macias Garcia

An example operation may include one or more of computing historical patterns related to fraudulent attempts from a transaction log, predicting future fraud attempts from public data, correlating the historical patterns and the predicted future fraud attempts, modifying one or more first endorsement policies based on the correlations, preventing modifying one or more second endorsement policies, the one or more second endorsement policies providing read-only access, and adding the modified one or more first endorsement policies to a smart contract.

Smart contract endorsement architecture

In an approach to automatic device enrollment in an IoT network, responsive to receiving a request to add a new device to an IoT network, device metadata is requested from the new device. Responsive to receiving the device metadata, the device metadata is confirmed with the device manufacturer using secure information services. Responsive to confirming the device metadata with the device manufacturer, configuration data for the new device is gathered from a repository, where the configuration data is gathered from devices with a same context type in the repository. Responsive to gathering the configuration data for the new device from the repository, the new device is enrolled in the IoT network using the configuration data.

Automatic device enrollment in an internet of things network

An example operation may include one or more of receiving sensor data from one or more sensors associated with a building, storing a block including the sensor data to a shared ledger of a blockchain network, the one or more sensors associated with one or more buildings, requesting a risk assessment for the sensor data, by a blockchain node, calculating the risk assessment with one or more machine learning algorithms based on the sensor data, historical sensor blockchain data, importance of the one or more sensors, and a degree of concern related to the sensor data, providing the risk assessment to the blockchain node, and generating an alert in response to the risk assessment above a threshold.

Sensor risk assessment database

Embodiments relate to virtualization of digital crown actions based on actions performed with an electronic pen. A technique includes communicatively coupling a smartwatch to an electronic pen, the smartwatch including a rotatable piece, where the rotatable piece controls a plurality of functionalities of the smartwatch. The technique includes receiving data from the electronic pen, and in response to receiving the data from the electronic pen, controlling at least one of the plurality of functionalities.

Virtualization of digital crown actions based on actions performed with an electronic pen

An example operation may include one or more of computing historical patterns related to fraudulent attempts from a transaction log, predicting future fraud attempts from public data, correlating the historical patterns and the predicted future fraud attempts, modifying one or more endorsement policies based on the correlations, and adding the modified one or more endorsement policies to a smart contract.

Auto-evolving database endorsement policies

Cognitive assistants which use feedback to highlight relevant points of interest to a user so that recommendations can be provided to the user based upon learned knowledge of the users preferences, tastes and customs are provided. For this purpose a computer-implemented method includes capturing user data of a user from a plurality of sensors, determining a cognitive state of the user from the captured data, correlating the user data to the cognitive state of the user, and making recommendations to the user based on the correlation of the user data and the determined cognitive state of the user.

Cognitive assistant with recommendation capability

Methods and systems are disclosed for encoding and decoding data from genetic traits. In one embodiment, the invention provides a method of encoding data from genetic traits. The method comprises encoding genetic traits information, including using quantum dot wavelengths to identify distinct genetic traits, and using numbers of the quantum dots to represent probabilities associated with the traits. In an embodiment, the invention provides a genetic characteristics decoding system for decoding genetic information encoded using quantum dots in a carrier. The decoding system comprises a light source for charging the quantum dots in the carrier; a scanner for scanning the carrier to retrieve information from the charged quantum dots; and a processing system for processing the retrieved information to determine quantum dot wavelengths to identify distinct genetic traits, and to determine numbers of the quantum dots to identify probabilities associated with the genetic traits.

Encoding data from genetic traits relevant to illness diagnosis and heritage

An object approaching a wearable device of a user is identified. In response to determining that the approaching object is a previously identified target of the user, one or more applications displayed in a user interface of the wearable device, and how said one or more applications are organized on the user interface of the wearable device, are modified based on the identified approaching object. The modified user interface is displayed to the user.

Finger control of wearable devices

Techniques are described with regard to client authentication management. An associated method includes constructing an authentication resolution model specific to a client based upon error patterns respectively included in a plurality of erroneous authentication submissions inconsistent with a proper authentication submission. The method further includes receiving, via an authentication interface, a new erroneous authentication submission inconsistent with the proper authentication submission. Responsive to determining that the new erroneous authentication submission corresponds to an authentication exception defined in the authentication resolution model, the method further includes completing authentication. Responsive to determining that the new erroneous authentication submission corresponds to an authentication warning defined in the authentication resolution model, the method further includes performing at least one client account warning protection activity. Responsive to determining that the new erroneous authentication submission corresponds to an authentication attack defined in the authentication resolution model, performing at least one client account attack protection activity.

Client authentication management based upon modeling

In an approach, a processor receives from a network device a request. A processor obtains from a database a device profile for the network device. A processor determines whether the device profile of the network device has a data usage pattern related to data identified by a data identifier. In response to determining the device profile has a related data usage pattern, a processor receives the related data usage pattern from the database. In response to determining the device profile does not have a related data usage pattern, a processor obtains a device type profile from the database. A processor classifies the data usage request based on at least one of the device profile and the device type profile. A processor executes a security action based on the classification of the data usage request. A processor stores the data usage request and executed security action to the database.

Managing data and data usage in IoT network

A method and system for automatically controlling a vehicle is provided. The method includes generating an original route of travel for a first vehicle for travel from an original location to a destination location. The vehicle is directed from the original location to the destination location such that the vehicle initiates motion and navigates the original route of travel towards the destination location in accordance with the original route of travel. Monitored vehicular attributes of the first vehicle are received and environmental attributes associated with the original route of travel are monitored with respect the first vehicle. Navigational issues associated with the vehicle traveling along the original route of travel are determined based on the monitored vehicular attributes and results of monitoring the environmental attributes. The navigational issues are used to determine if the vehicle should continue to travel along the original route of travel.

Automated vehicle control

The disclosure describes techniques for generating device recommendations. The techniques include registering a plurality of Internet of Things (IoT) devices in a social IoT network, where each device performs one or more tasks and the one or more tasks include a first task. The techniques include periodically receiving, with the social IoT network, a work profile from one or more of the registered devices. The work profile includes device information associated with the one or more device tasks performed by the respective registered device. The techniques include grouping devices performing the first task into groups of similar devices, identifying, based on the device information in the work profile received from one or more of the registered devices, at least one device from the group of devices for which recommendations are to be provided, generating the recommendations for the identified device, and providing the recommendations for the identified device.

Device recommendations based on device interactions in network

Disclosed embodiments provide techniques for computer networks infrastructure automatic convergence. The network devices are enabled to communicate with other adjacent network devices, independently of the device type, about detected changes that could affect them and together generate consensus utilizing a blockchain mechanism about the configuration changes that are accepted. A priority table specifies a priority for various device classes on a network. The devices, in response to a new network topology, determine if a new device configuration is necessary. When a new device configuration is necessary, data corresponding to the new device configuration is put into a blockchain block and appended to a network blockchain that is maintained by one or more nodes (devices) on the network. In this way, an immutable history of network configurations is maintained, improving network security and reliability.

System and method for network infrastructure analysis and convergence

Embodiments are disclosed for preventing network attacks. The techniques include generating a usage profile for a computing device that accesses a network. The techniques also include determining a plurality of actual use real-time indicators for a network connection on the network. The techniques further include determining a plurality of expected use real-time indicators for the network connection. Additionally, the techniques include calculating a risk assessment value for the network connection based on the actual use real-time indicators and the expected use real-time indicators. Further, the techniques include performing a security action for the network connection based on the calculated risk assessment value.

Preventing network attacks

In a computer implemented approach for securely updating vehicle software the computer monitors data associated with a vehicle, determines that a software update is necessary, requests validation of a software update, receives validation of the software update from the network, updates the vehicle software with the received software update, receives an updated blockchain ledger entry associated with the vehicle, and utilizes the updated vehicle software to control the vehicle.

Multi-variable based secure download of vehicle updates

Growing community of inventors

Heredia, Costa Rica

Edgar Adolfo Zamora Duran