Abstract: An apparatus is provided, where the apparatus includes a plurality of components; a first sensing system to measure first power consumed by first one or more components of the plurality of components; a second sensing system to measure second power consumed by the apparatus; an analog-to-digital converter (ADC) to generate an identification (ID) that is representative of the second power consumed by the apparatus; and a controller to allocate power budget to one or more components of the plurality of components, based on the measurement of the first power and the ID.

Abstract: Systems and methods are provided for collecting anonymized drive information. A processing device may be configured to receive outputs from one or more sensors; determine at least one motion representation for the host vehicle based on the outputs; receive at least one image representative of an environment of the host vehicle; analyze the at least one image to determine at least one road characteristic associated with a road section; assemble first road segment information relative to a first portion of the road section, wherein the first portion of the road section is separated from a starting point associated with a route traveled by the host vehicle; assemble second road segment information relative to a second portion of the road section; and cause transmission of the first road segment information and the second road segment information to a server for assembly of an autonomous vehicle road navigation model.

Abstract: In performance testing a data storage system, operating parameters and performance data are recorded as the system executes performance tests over a test period, where the performance data includes measures of a performance characteristic (e.g., latency) across a range of I/O operation rates or I/O data rates for each performance test. Subsets of recorded operating parameters and performance data are selected and applied to a machine learning model to train and use the model, and the model provides a model output indicative for each performance test of a level of validity of the corresponding performance data. Based on the model output indicating at least a predetermined level of validity for a given performance test, the performance data for the performance test are incorporated into a record of validated performance data for the data storage system, usable for benchmarking, regression analysis, hardware qualification, etc.

Abstract: Performance testing a data storage system includes recording operating parameters and performance data as the data storage system executes performance tests over a test period, the performance data including one or more measures of a performance characteristic (e.g., latency) across a range of I/O operation rates or I/O data rates for each of the performance tests. Subsets of recorded operating parameters and performance data are selected and applied to a machine learning model to train and use the model, and the model provides a model output indicative for each performance test of a level of validity of the corresponding performance data. Based on the model output indicating at least a predetermined level of validity for a given performance test, the performance data for the performance test are incorporated into a record of validated performance data for the data storage system, usable for benchmarking, regression analysis, hardware qualification, etc.

Abstract: A method and system for protecting an application from unsecure network exposure. The method includes identifying an at-risk application, wherein identifying the at-risk application further comprises determining that the application is configured incorrectly; identifying at least one port through which the at-risk application is accessible when the at-risk application is determined to be configured incorrectly; and determining, based on the identified at least one port through which the at-risk application is accessible, whether an exposure vulnerability exists, wherein the exposure vulnerability is an unapproved exposure of at least one of the at least one port to external resources.

Abstract: A method and system for protecting an application from unsecure network exposure. The method includes identifying at least one port through which the application is accessible when the application is not configured correctly, wherein the application is executed at a host device connected to at least one network, the host device having the at least one port; sending, to an external resource, connection data for connecting to the application via the at least one port, wherein the external resource is configured to attempt to connect to the application based on the connection data and to return results of the connection attempt; determining, based on the results of the connection attempt, whether an exposure vulnerability exists; and performing at least one mitigation action when an exposure vulnerability exists.

Abstract: A method and system for protecting an application from unsecure network exposure. The method includes identifying at least one port through which the application is accessible when the application is not configured correctly, wherein the application is executed at a host device connected to at least one network, the host device having the at least one port; sending, to an external resource, connection data for connecting to the application via the at least one port, wherein the external resource is configured to attempt to connect to the application based on the connection data and to return results of the connection attempt; determining, based on the results of the connection attempt, whether an exposure vulnerability exists; and performing at least one mitigation action when an exposure vulnerability exists.