International Business Machines Corporation

Timothy James Hahn

Michael Bender

Rhonda L Childress

Marc Dickenson

Heather Maria Hinton

Rahul Gupta

David B Kumhyr

Thomas J Fleischman

James J Whitmore

Michael P Waidner

Leucir Marin, Jr

Bernard Paul Palmer, Jr

Leucir Marin Junior

Glen Alan Jaquette

David Louis Kaminsky

Ying Liu

Zhi Hu Wang

David Mark Ogle

Peng Ji

Jeffrey Alan Frey

Hari Haranath Madduri

Xinlin Wang

Xi Ning Wang

Tian Zhang

Richard Henry Guski

Viswanath Srikanth

Patrick S Botz

Joshua M Small

Theodore R Maeurer

Brian J Lang

Shao M Geng

Jun Zhu

Andrew Ronald Freed

Jian Ding

Ching-Yun Chao

Nataraj Nagaratnam

Robert Haas

Donna N Dillenberger

Ilias Iliadis

Anthony Joseph Nadalin

Paul Merrill Greco

Joanna W Ng

John C Dayka

Dieter Buehler

Kathryn Heninger Britton

Patrick Ryan Wardrop

Jeffrey Mark Achtermann

David Gerard Kuehr-McLaren

Mark A Nelson

Michael E Baskey

John Ryan McGarvey

Yi-hsiu Wei

Gary Stuart Puchkoff

Dilip Dinkar Kandlur

Chunhui Yang

Christian Cachin

Barry Keith Aldred

Henry C Will, Iv

John Thomas Peck

Xiaoyu Hu

David Andrew Booz

Rene Pawlitzek

Isa M Torres

Patrick Jerome Fleming

Ellen Jean Stokes

Michael P Robertson

Harrison Kurtz

Margaret K LaBelle

Charles Spencer Brown

Jarrod R Anderson

Blockchain based IoT data management can include receiving IoT data are with one or more processing units. At least one aggregation pattern of the IoT data can be determined by one or more processing units. The IoT data can be hashed, based upon the at least one aggregation pattern to obtain hash values of the IoT data by one or more processing units. The hash values can be sent to a blockchain system for storing by one or more processing units.

Blockchain based IOT data management

An example operation may include one or more of determining an energy state of a system, generating a wireless energy transfer request based on the energy state, transmitting the wireless energy transfer request to another system, receiving wireless energy transfer information from the other system, performing a wireless energy exchange with the other system based on the wireless energy transfer information, and receiving a data block associated with the wireless energy exchange from the other system.

Wireless energy transfer

Techniques are provided for blockchain based a data transformation. According to one aspect, a series of Internet of Things (IoT) data is received by one or more processing units. And at least one reference data set to the received series of IoT data are attached by one or more processing units. The received series of IoT data attached are processed, by one or more processing units, with at least one transformation module to obtain a processing result of the at least one reference data set. A hash value of the processing result is calculated by one or more processing units. The hash value of the processing result and a hash value of an expected result stored in a blockchain system are compared. In respond to the hash value of the processing result being not matched with the hash value of the expected result, the decision of the at least one transformation module having been tampered with is determined by one or more processing units.

Blockchain based data transformation

According to one embodiment of the present invention, a system provides security for a device and includes at least one processor. The system monitors a plurality of networked devices for a security risk. Each networked device is associated with a corresponding security risk tolerance. In response to a monitored security risk for one or more of the plurality of networked devices exceeding the corresponding risk tolerance, a network service is initiated to perform one or more actions on each of the one or more networked devices to alleviate the associated security risk. Embodiments of the present invention further include a method and computer program product for providing security to a device in substantially the same manner described above.

Security for devices connected to a network

A computer-implemented method for vehicle to vehicle messaging. The method captures a voice command of a user in a first vehicle, and extracts an intent, a target recipient, and a message payload from the captured voice command of the user, using natural language processing. The method further analyzes video content from one or more cameras of the first vehicle, and identifies the target recipient relevant to the captured voice command, based on the analyzed video content. The method further transmits the message payload to the identified target recipient based on the extracted intent. In one embodiment, the message payload is transmitted to the target recipient via peer-to-peer communication, together with one or more segments of the analyzed video content and is displayed on a user interface of the identified target recipient.

Vehicle to vehicle messaging

Methods and apparatus, including computer program products, implementing and using techniques for enhancing the security of Internet of Things (IoT) devices. A homogenous and leaderless group of IoT devices sharing one or more common features is defined. During operation of the IoT devices, it is identified whether an IoT device in the group operates outside an expected tolerance for the operation of the IoT devices in the group. In response to identifying that an IoT device in the group operates outside an expected tolerance, an action is performed on the IoT device.

Security for internet of things devices

Provided are techniques for grouping devices as a virtual device for providing better quality of device data. A group of devices in an Internet of Things (IoT) network is identified based on one or more attributes of each of the devices. The group of devices is provided as a single virtual device by: collecting data from each of the devices in the group, transforming the data, and using the transformed data to modify a device.

Grouping devices as a virtual device for providing better quality of device data

Determining a type of actor performing an activity includes monitoring the performance of the activity via at least one sensor to produce activity readings over a dimension. The activity readings are then compared to reference readings that are generated based on a machine performing same activity. The comparison of the reference readings to the activity readings is used to determine a variance between the activity readings and reference readings. Once the variance is determined, the variance is compared with a threshold value to determine the type of actor performing the activity.

Monitoring an activity and determining the type of actor performing the activity

Provided are techniques for mitigating security risks utilizing continuous device image reload with data integrity. Continuous reload of a first image on a device in an Internet of Things (IoT) group of devices coupled to an IoT service is performed based on triggers. A trigger from the triggers is received that indicates one of that a period of time has expired, that notification of a known infection has been received, and that there has been failure of an internal onboard security check. A second image is obtained that is not infected from the IoT service. The device is reloaded with the second image to replace the first image with the second image.

Mitigating security risks utilizing continuous device image reload with data integrity

In a method for device unavailability management within a network, a network device selects an advocate device as an agent of the network device. The network device defines a set of actions to be executed when the network device ever becomes unavailable. The set of actions is stored in a datastore and associated with the network device. Upon determining that the network device has become unavailable, the advocate device is notified and obtains the set of actions associated with the network device. The advocate device then executes the set of actions by the advocate device.

Devices demise actions and notification

A method, a device and a computer program product are provided. A networked device determines whether a condition occurred. In response to detecting the condition, the networked device requests information to update a current credential of the networked device. The networked device updates the current credential with the requested information to maintain security of the networked device. The networked device accesses at least one networked service based on the updated credential. The current credential includes either a cryptographic key or a password. When the current credential includes the password, the condition includes a usage rate including one or more from a group of a quantity of reboot commands for the networked device and a quantity of software update commands for the networked device.

Self management of credentials by IoT devices

In the sharing of data between connected devices over a network, a network device broadcasts an availability of a set of data collected by a data producing device coupled to the network. The network device receives a request to access the set of data from a data consuming device coupled to the network, and a cognitive computing module of the network device determines a set of terms between the data producing and the data consuming devices for access to the set of data. In response, the network device obtains the set of data and a first key from the data producing device. Upon receiving a second key from the data consuming device, the network device determines that the second key is associated with the first key. In response, the network device provides access to the set of data to the data consuming device according to the set of terms.

Sharing of anonymous data between connected devices over the internet

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Cary, NC, United States of America

Timothy James Hahn