Abstract: This disclosure describes techniques for device authentication and/or pairing. A display system can comprise a head mountable display, computer memory, and processor(s). In response to receiving a request to authenticate a connection between the display system and a companion device (e.g., controller or other computer device), first data may be determined, the first data based at least partly on biometric data associated with a user. The first data may be sent to an authentication device configured to compare the first data to second data received from the companion device, the second data based at least partly on the biometric data. Based at least partly on a correspondence between the first and second data, the authentication device can send a confirmation to the display system to permit communication between the display system and companion device.

Abstract: This disclosure describes techniques for device authentication and/or pairing. A display system can comprise a head mountable display, computer memory, and processor(s). In response to receiving a request to authenticate a connection between the display system and a companion device (e.g., controller or other computer device), first data may be determined, the first data based at least partly on audio data spoken by a user. The first data may be sent to an authentication device configured to compare the first data to second data received from the companion device, the second data based at least partly on the audio data. Based at least partly on a correspondence between the first and second data, the authentication device can send a confirmation to the display system to permit communication between the display system and companion device.

Abstract: The disclosure is generally directed to a method and system for charge station management including collecting data related to a plurality of charge stations, the data identifying location data, an operator, and a data provider for each of the plurality of charge stations, collating the data to match the location data with the operators of each of the plurality of charge stations, and merging the location data based on a set of criteria including the data from each of the data providers within an identified geohash location. Merging includes setting a geohash about a data provider, and merging location data within the predetermined perimeter to remove redundant locations based on a set of criteria, including criteria identifying a same operator within the geohash.

Abstract: The disclosure is generally directed to a method and system for charge station management including collecting data related to a plurality of charge stations, the data identifying location data, an operator, and a data provider for each of the plurality of charge stations; collating the data to match the location data with the operators of each of the plurality of charge stations; and sequentially merging the location data based on a set of criteria including the data from each of the data providers within a predetermined configurable radius defining a perimeter surrounding each data provider-identified location. Collecting raw data includes receiving the raw data from crowd-sourced data providers; receiving the raw data from the operators of the plurality of charge stations; and organizing the raw data as batch data.

Abstract: A computer-implemented method for privacy preserving authentication augmented with physical biometric proof is disclosed. The computer-implemented method comprises providing an integrated smart entity comprising both, a visual indicator of a physical entity and a persistent memory storing picture identifier data. The visual indicator and the persistent memory are physically inseparable. The computer-implemented method further comprises comparing the visual indicator and a related feature of the physical entity to be authenticated, receiving an output value of a function having the picture identifier data as argument and a verifiable credential. Upon determining that the output value of the function and the received verifiable credential are satisfy a matching predicate, confirming the verifiable credential.

Abstract: A switching unit (200) including a membrane (202), a housing (210), at least one rotary switch (204), at least one knob (216), and a sealing member (214). The membrane (202) defines a first opening (230) adapted to receive a portion of at least one rotary switch (204). The housing (210) defines a second opening adapted to be aligned with the first opening (230) to receive the portion of the at least one rotary switch (204). The at least one rotary switch (204) is disposed in the housing (210). The at least one knob (216) mounted on the at least one rotary switch (204). The sealing member (214) is positioned on the housing (210) in the second opening (231), around the at least one rotary switch (204), between the at least one knob (216) and the housing (210).

Abstract: One embodiment provides a method, including: receiving, from a user at a collaboration platform, a request to perform a computation; generating a workflow comprising a sequence of steps for performing the computation; identifying potential data sources comprising the type of data and able to assist in performing at least one of the sequence of steps of the workflow; selecting computation data sources that collaborate to perform the computation, wherein the selecting is performed dynamically and based upon characteristics of a network created by the collaboration platform and between the computation data sources; and facilitating performance of the computation by the computation data sources using data of the computation data sources, wherein during performance of the computation the computation data sources collaborate within the network to perform the workflow while maintaining individual privacy of the data of the computation data sources and providing proof verifying a trustworthiness of the computation.

Abstract: This disclosure describes techniques for device authentication and/or pairing. A display system can comprise a head mountable display, computer memory, and processor(s). In response to receiving a request to authenticate a connection between the display system and a companion device (e.g., controller or other computer device), first data may be determined, the first data based at least partly on audio data spoken by a user. The first data may be sent to an authentication device configured to compare the first data to second data received from the companion device, the second data based at least partly on the audio data. Based at least partly on a correspondence between the first and second data, the authentication device can send a confirmation to the display system to permit communication between the display system and companion device.

Abstract: Disclosed herein are systems and methods for device authentication or pairing. In an aspect, a wearable display system comprises a display, an image capture device configured to capture images of a companion device, a computer-readable storage medium configured to store the images of the companion device, and a processor in communication with the image capture device and the storage medium. The processor can be programmed with executable instructions to receive a first image of a first optical pattern displayed by the companion device captured by the image capture device, wherein the first optical pattern is generated by the companion device based on first shared data, extract first data from the first optical pattern in the received first image, authenticate the companion device based on the first data extracted from the first optical pattern, and notify a user of the wearable display system that the companion device is authenticated.

Abstract: There is provided a system and a method comprising obtaining a sequence of a plurality of frames of an area of a specimen, wherein at least one frame of the sequence is transformed with respect to another frame, obtaining a reference frame based at least on a first frame of the sequence, determining, based on the reference frame, a reference pattern, wherein the reference pattern is informative of a structural feature of the specimen in the area, for a given frame of the sequence, determining, based on the given frame, a pattern informative of said structural feature in the area, determining data Dshrinkage informative of an amplitude of a spatial transformation between the reference pattern and the pattern, generating a corrected frame based on said pattern and Dshrinkage and generating an image of the area.

Abstract: One embodiment provides a method, including: receiving, at a service provider and from a user, a request for computation of a function, wherein the request includes a description of the function to be computed and requirements of the user; identifying, from data sources accessible to the service provider, a plurality of data sources to participate in the computation in view of the requirements and the description of the function, wherein each of the plurality of data sources includes data of a data owner and constraints on use of the data; identifying a multi-party computation protocol and parameters of the multi-party computation protocol for performing the computation; and running the computation of the function using the data of the plurality of data sources and in view of the requirements of the user and the constraints of the plurality of data sources.

Abstract: An example operation may include one or more of generating, by an executing client, a blockchain transaction comprising an anonymous rating, a proof, a nullifier, and a root node value, receiving, by a smart contract, the blockchain transaction, the anonymous rating related to an authorizing client, verifying the proof with the root node value and the nullifier, verifying that the root node value is a current or a previous merkle tree root node value, adding the anonymous rating to a shared ledger, marking the nullifier as used, and storing the marked nullifier to the shared ledger.

Abstract: One embodiment provides a method, including: receiving, at a service provider and from a user, a request for computation of a function, wherein the request includes a description of the function to be computed and requirements of the user; identifying, from data sources accessible to the service provider, a plurality of data sources to participate in the computation in view of the requirements and the description of the function, wherein each of the plurality of data sources includes data of a data owner and constraints on use of the data; identifying a multi-party computation protocol and parameters of the multi-party computation protocol for performing the computation; and running the computation of the function using the data of the plurality of data sources and in view of the requirements of the user and the constraints of the plurality of data sources.

Abstract: One embodiment provides a method, including: receiving, from a user at a collaboration platform, a request to perform a computation; generating a workflow comprising a sequence of steps for performing the computation; identifying potential data sources comprising the type of data and able to assist in performing at least one of the sequence of steps of the workflow; selecting computation data sources that collaborate to perform the computation, wherein the selecting is performed dynamically and based upon characteristics of a network created by the collaboration platform and between the computation data sources; and facilitating performance of the computation by the computation data sources using data of the computation data sources, wherein during performance of the computation the computation data sources collaborate within the network to perform the workflow while maintaining individual privacy of the data of the computation data sources and providing proof verifying a trustworthiness of the computation.

Abstract: Network identifiers are extracted from route advertisements. A table associates virtual network identifiers with provider edge devices. When a virtual network identifier extracted from a route advertisement matches a virtual network identifier in the table, the route advertisement is propagated to the provider edge devices associated with that virtual network identifier in the table. The route advertisement is not propagated to provider edge devices not associated with that virtual network identifier in the table.

Abstract: An example operation may include one or more of receiving, from an executing client, a blockchain transaction comprising an anonymous rating related to an authorizing client, a merkle tree root node value, a proof, and a nullifier, and in response, executing, by a smart contract, a valid historical value assert call on a lookback key storing the merkle tree root node value, verifying, through a valid historical value assert call, that the merkle tree root node value is a current or previous value of the merkle tree root node value, verifying the proof with the merkle tree root node value and the nullifier, adding the anonymous rating to a shared ledger, marking the nullifier as used, and storing the marked nullifier to the shared ledger.

Abstract: Network identifiers are extracted from route advertisements. A table associates virtual network identifiers with provider edge devices. When a virtual network identifier extracted from a route advertisement matches a virtual network identifier in the table, the route advertisement is propagated to the provider edge devices associated with that virtual network identifier in the table. The route advertisement is not propagated to provider edge devices not associated with that virtual network identifier in the table.

Abstract: Methods, systems, and computer program products for verifying confidential machine learning models are provided herein. A computer-implemented method includes obtaining (i) a set of training data and (ii) a request, from a requestor, for a machine learning model, wherein the request is accompanied by at least a set of test data; obtaining a commitment from a provider in response to the request, the commitment comprising a special hash corresponding to parameters of a candidate machine learning model trained on the set of training data; revealing the set of test data to the requestor; obtaining, from the requestor, (i) a claim of performance of the candidate machine learning model for the test data and (ii) a proof of the performance of the candidate machine learning model; and verifying the claimed performance for the requestor based on (i) the special hash and (ii) the proof of the claimed performance.

Abstract: There is provided a system and a method comprising obtaining a sequence of a plurality of frames of an area of a specimen, wherein at least one frame of the sequence is transformed with respect to another frame, obtaining a reference frame based at least on a first frame of the sequence, determining, based on the reference frame, a reference pattern, wherein the reference pattern is informative of a structural feature of the specimen in the area, for a given frame of the sequence, determining, based on the given frame, a pattern informative of said structural feature in the area, determining data Dshrinkage informative of an amplitude of a spatial transformation between the reference pattern and the pattern, generating a corrected frame based on said pattern and Dshrinkage and generating an image of the area.