Abstract: A computer-implemented method for mitigating anomalous activity in an embedded computer system including a plurality of communicably coupled embedded processing elements. The method includes: detecting a transmission of an anomalous message in the embedded computer system; transmitting at least one notification to a plurality of embedded processing elements in the embedded computer system, wherein the notification is encrypted using a cryptographic key; in at least one embedded processing element of the plurality of processing elements: receiving the at least one notification; identifying, at the at least one embedded processing element, that the at least one notification has been encrypted using the cryptographic key; and reconfiguring the at least one processing element from a first mode into a second mode, wherein the at least one processing element presents a reduced functionality to the embedded computer system in the second mode.

Abstract: A method for providing a function by a group of computing units in which computation instances are executed, each computation instance implementing the function using at least one algorithm and being set up to determine at least one result in response to a call of the function. The method includes: determining an integrity level for each of the computation instances; receiving a function request from a subscriber, the function request including a quality requirement that includes an integrity requirement; selecting a plurality of the computation instances corresponding to the quality requirement, so that the integrity level of the selected computation instances corresponds to the integrity requirement; calling the function in the selected computation instances corresponding to the function request in order to determine a plurality of results; determining a response based on the results, taking into account the quality requirement; and sending the response to the subscriber.

Abstract: An apparatus and computer-implemented method for allocating computing resources in a method for protecting a computer-aided development environment in a distributed development process from damage and threats. In the method for protecting, multiple methods for identifying damage and/or a threat in the computer-aided development environment are carried out, wherein a metric which quantifies a quality and/or informative value of the method is determined for each method, wherein a respective offer for allocating computing resources for the execution of the respective method is determined for the methods depending on said metric, wherein the computing resources are allocated to the methods depending on the respective offer.

Abstract: A method for manufacturing a faucet body (1) for a sanitary faucet, having at least the following steps: a) production of the faucet body (1) in an injection mold, wherein the injection mold at least partially forms a brushed texture (3) on a surface (2) of the faucet body (1); b) coating the faucet body (1) with at least one first layer (4) comprising copper; and c) coating the faucet body (2) with at least one second layer (5) comprising a nickel-phosphorus alloy. A faucet body of plastic for a sanitary faucet is also proposed.

Abstract: Methods and systems for securely managing personal data associated with image processing include an image sensor configured to capture an image, a local computer system local to the image sensor, and a backend computer system remote from the image sensor. The local computer system has a processor with a trusted execution environment (TEE) that detects anomalies in images from the image sensor, extracts personal data from the image, and encrypts the personal data. The local computer system then sends the extracted, encrypted personal data to the backend computer system, where a backend TEE decrypts the extracted, encrypted personal data, and performs data processing by comparing the decrypted personal data to other personal data that is stored in a backend database in the backend computer system.

Abstract: A system and method are disclosed for processing data subject rights requests. The system and method advantageously enable data controllers to train machine learning models on unaltered data having PII, while maintaining the privacy of the unaltered data and enabling compliance with data subject rights requests with respect to the data. The system and method incorporate a biometric database that stores biometric data extracted from the unaltered data having PII. In order to identify data relating to a data subject rights request, biometric data is received from the data subject and is matched against the biometric data stored in the biometric database. Based on the matched biometric data, the original unaltered source data having PII can be identified for the purpose of exercising one or more data subject rights, such as erasure, access, and objection to processing.

Abstract: A method for providing a function via a network of processing units using multiple computing instances. Each computing instance implements the function and is configured, when it is executed, to determine at least one result in response to a call-up of the function. The method includes validating the computing instances, each being checked as to whether the computing instance corresponds to a respective predetermined state; determining a respective level of reliability for each of the processing units; starting execution of successfully validated computing instances in the processing units, which have a level of reliability that is equal/greater than a predetermined minimum level of reliability; receiving a function request from a user; calling up the function in at least a portion of the executed computing instances corresponding to the function request, in order to determine multiple results; determining a response based on the results; and sending the response to the user.

Abstract: A load protection apparatus for protecting an electrical load connected to an output terminal of the load protection apparatus against overcurrent, includes an overcurrent protection circuit having a power switch through which the electrical load receives an electrical load current via the output terminal and having a sensor component connected in series with the power switch. The sensor component is adapted to directly generate a voltage drop corresponding to the current rise speed of the electrical load current flowing from an input terminal of the load control apparatus, via the sensor component and the power switch to the output terminal. The sensor component further includes a driver circuit adapted to detect an occurring overcurrent depending on the voltage drop generated by the sensor component and depending on a voltage drop along the power switch adapted to switch off said power switch upon detection of an overcurrent within a switch-off period.

Abstract: A motor control apparatus for controlling a power supply to an electrical motor (M) connected to an output terminal (3) of the motor control apparatus (1) comprising: an overcurrent protection circuit (1A) having a power switch (5) through which the electrical motor (M) receives an electrical load current (IL) and having a sensor component (4) connected in series with the power switch (5) and adapted to generate directly a voltage drop (?U4) corresponding to the current rise speed of the electrical load current (IL) flowing from an input terminal (2) of the motor control apparatus (1) via the sensor component (4) and the power switch (5) to the output terminal (3) and having a driver circuit (6) adapted to detect an occurring overcurrent depending on the voltage drop (?U4) generated by the sensor component (4) and/or depending on a voltage drop (?U5) along the power switch (5) and adapted to switch off said power switch (5) upon detection of an overcurrent within a switch-off period of less than one millisec

Abstract: A load control apparatus for controlling a power supply to an electrical load connected to an output terminal includes an overcurrent protection circuit having a power switch through which the electrical load receives a load current and a sensor component in series with the power switch that is configured to generate a voltage drop corresponding to the current rise speed of a load current from an input terminal to the output terminal. The protection circuit includes a driver circuit configured to detect an overcurrent depending on the voltage drop generated by the sensor component and/or at the power switch, and to switch off the power switch upon detection of an overcurrent within a switch-off period. The overcurrent protection circuit can include a power supply control circuit having a sensor component adapted to measure a supply voltage notified to a control unit of the load control apparatus adapted to control power supplied to the load.

Abstract: A plumbing component (1) having a coating (2) with an outer layer (3), wherein the outer layer (3) is at least partially made of copper or a copper alloy. In addition, a method for coating the plumbing component (1).

Abstract: A method for coating a plumbing component (1), comprising at least the following steps: a) providing the plumbing component (1), wherein the plumbing component (1) has at least one liquid channel (2); and b) at least partially coating an inner surface (3) of the at least one liquid channel (2) with a coating (4), wherein the coating (4) has at least one layer (5), which comprises copper.

Abstract: Disclosed are systems and methods for a computerized framework that provides an improved, secure computational environment between trusted and untrusted devices (e.g., a Trusted Execution Environment (TEE) and graphics processing unit (GPU), respectively) for executing and offloading Convolutional Neural Network (CNN) computations and operations. The disclosed framework can operate to perform such secure offloading and processing not only during inference computations of the CNN, but also during training of the CNN. The disclosed framework operates to enable training and execution of CNN models, whereby the data used for such operations are held securely while they are in use, in transit (e.g., between the TEE and GPU) and while in storage.

Abstract: Methods and systems of leveraging multiple data-collection entities to protect personal data. Image data is captured via an image sensor of a vehicle. A classifier can partition the captured image data into personal data and non-personal data, and can assign a confidence score to the personal data. If the confidence score is below a threshold, the vehicle can broadcast a wireless signal to other data-collection entities such as other vehicles or road-side unit, wherein the wireless signal includes a request for the other data-collection entities to inform the vehicle if those data-collection entities have detected personal data at a time corresponding to when the image sensor of the vehicle captured the image data. If the other data-collection entities indeed detected such personal data at the time, the vehicle can perform various actions such as deleting the images, or the portions that include personal data.

Abstract: Methods and systems for securely managing personal data associated with image processing include an image sensor configured to capture an image, a local computer system local to the image sensor, and a backend computer system remote from the image sensor. The local computer system has a processor with a trusted execution environment (TEE) that detects anomalies in images from the image sensor, extracts personal data from the image, and encrypts the personal data. The local computer system then sends the extracted, encrypted personal data to the backend computer system, where a backend TEE decrypts the extracted, encrypted personal data, and performs data processing by comparing the decrypted personal data to other personal data that is stored in a backend database in the backend computer system.

Abstract: A method for communicating data requests to one or more data sources. The method includes receiving a data request, with which data of one or more data types are requested, from an application, and checking the availability of one or more data sources that are able to provide the one or more requested data types. The method further comprises: if at least one of the one or more data sources is available, sending a request to the available data source for the requested associated data type that the data source can provide; and, if no data source is available for at least one of the requested data types, sending a request for this data type to a placeholder module.

Abstract: A system and method are disclosed for processing data subject rights requests. The system and method advantageously enable data controllers to train machine learning models on unaltered data having PII, while maintaining the privacy of the unaltered data and enabling compliance with data subject rights requests with respect to the data. The system and method incorporate a biometric database that stores biometric data extracted from the unaltered data having PII. In order to identify data relating to a data subject rights request, biometric data is received from the data subject and is matched against the biometric data stored in the biometric database. Based on the matched biometric data, the original unaltered source data having PII can be identified for the purpose of exercising one or more data subject rights, such as erasure, access, and objection to processing.

Abstract: A method for providing a function via a network of processing units using multiple computing instances. Each computing instance implements the function and is configured, when it is executed, to determine at least one result in response to a call-up of the function. The method includes validating the computing instances, each being checked as to whether the computing instance corresponds to a respective predetermined state; determining a respective level of reliability for each of the processing units; starting execution of successfully validated computing instances in the processing units, which have a level of reliability that is equal/greater than a predetermined minimum level of reliability; receiving a function request from a user; calling up the function in at least a portion of the executed computing instances corresponding to the function request, in order to determine multiple results; determining a response based on the results; and sending the response to the user.

Abstract: A method for providing a function by a group of computing units in which computation instances are executed, each computation instance implementing the function using at least one algorithm and being set up to determine at least one result in response to a call of the function. The method includes: determining an integrity level for each of the computation instances; receiving a function request from a subscriber, the function request including a quality requirement that includes an integrity requirement; selecting a plurality of the computation instances corresponding to the quality requirement, so that the integrity level of the selected computation instances corresponds to the integrity requirement; calling the function in the selected computation instances corresponding to the function request in order to determine a plurality of results; determining a response based on the results, taking into account the quality requirement; and sending the response to the subscriber.

Abstract: A method for communicating data requests to one or more data sources. The method includes receiving a data request, with which data of one or more data types are requested, from an application, and checking the availability of one or more data sources that are able to provide the one or more requested data types. The method further comprises: if at least one of the one or more data sources is available, sending a request to the available data source for the requested associated data type that the data source can provide; and, if no data source is available for at least one of the requested data types, sending a request for this data type to a placeholder module.