Abstract: Disclosed embodiments relate to opportunistically updating Electronic Control Unit (ECU) software in a vehicle. Operations may include receiving, at a controller in a vehicle, a wireless transmission indicating a need to update software running on at least one ECU in the vehicle; monitoring an operational status of the vehicle to determine whether the vehicle is in a first mode of operation in which an ECU software update is prohibited; delaying the ECU software update when the operational status is prohibited; continuing to monitor the operational status of the vehicle to determine whether the vehicle is in a second mode of operation in which the ECU software update is permitted; and enabling updating of the at least one ECU with the delayed ECU software update when it is determined that the vehicle is in the second mode of operations.

Abstract: Disclosed embodiments relate to perform operations for receiving and integrating a delta file in a vehicle. Operations may include receiving, at an Electronic Control Unit (ECU) in the vehicle, a delta file, the delta file comprising a plurality of deltas corresponding to a software update for software on the ECU and startup code for executing the delta file in the ECU; executing the delta file, based on the startup code, in the ECU; and updating memory addresses in the ECU to correspond to the plurality of deltas from the delta file.

Abstract: Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.

Abstract: Disclosed herein are techniques for visualizing and configuring controller function sequences.

Abstract: Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.

Abstract: Disclosed herein are techniques for efficiently providing controller data as part of a maintenance or update process. Techniques include receiving, from a first remote computing device, a message associated with at least one controller; extracting, based on the received message, an image of software associated with the at least one controller; accessing, based on the extracted image, a delta file; and transmitting the accessed delta file to a second remote computing device.

Abstract: Disclosed herein are techniques for analyzing control-flow integrity based on functional line-of-code behavior and relation models. Techniques include receiving data based on runtime operations of a controller; constructing a line-of-code behavior and relation model representing execution of functions on the controller based on the received data; constructing, based on the line-of-code behavioral and relation model, a dynamic control flow integrity model configured for the controller to enforce in real-time; and deploying the dynamic control flow integrity model to the controller.

Abstract: Disclosed embodiments relate to automatically providing updates to at least one vehicle, Operations may include receiving, at a server remote from the at least one vehicle, Electronic Control Unit (ECU) activity data from the at least one vehicle, the ECU activity data corresponding to actual operation of the ECU in the at least one vehicle; determining, at the server and based on the ECU activity data, a software vulnerability affecting the at least one vehicle, the software vulnerability being determined based on a deviation between the received ECU activity data and expected ECU activity data; identifying, at the server, an ECU software update based on the determined software vulnerability; and sending, from the server, a delta file configured to update software on tree ECU with a software update corresponding to the identified ECU software update.

Abstract: Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring, in the vehicle, data representing real-time processing activity of the ECU accessing, in the vehicle, historical data relating to processing activity of the ECU, the historical data representing expected processing activity of the ECU; comparing, in the vehicle, the real-time processing activity data with the historical data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.

Abstract: Disclosed herein are techniques for generating and signing line-of-code behavior and relation models. Techniques include identifying executable code for a controller; performing a functional analysis of the executable code to determine a plurality of functions associated with the executable code and a plurality of relationships between the plurality of functions; generating, based on the determined plurality of functions and plurality of relationships, a line-of-code behavior and relation model for the executable code; performing a signature operation on the generated line-of-code behavior and relation model to produce a unique signature value associated with at least one of: the line-of-code behavior and relation model or a functional block of the line-of-code behavior and relation model; and linking the unique signature value to the line-of-code behavior and relation model.

Abstract: Disclosed herein are techniques for analyzing hardware change impacts based on at least one functional line-of-code behavior and relation model. Techniques include identifying a new hardware component associated with a system; accessing a first line-of-code behavior and relation model representing execution of functions using the new hardware component; accessing a second line-of-code behavior and relation model representing execution of functions on a previous hardware component of the system; performing a functional differential comparison of the first line-of-code behavior and relation model to the second line-of-code behavior and relation model; determining, based on the functional differential comparison, a status of functional equivalence between the new hardware component and the previous hardware component; and generating, based on the determined difference, a report identifying the status of functional equivalence.

Abstract: Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring data representing real-time processing activity of the ECU; receiving comparable data relating to processing activity of at least one other ECU deemed comparable in functionality to the ECU; comparing the real-time processing activity data with the comparable data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.

Abstract: Disclosed herein are techniques for visualizing and configuring controller function sequences.

Abstract: Disclosed herein are techniques for efficiently providing controller data as part of a maintenance or update process. Techniques include receiving, from a first remote computing device, a message associated with at least one controller; extracting, based on the received message, an image of software associated with the at least one controller; accessing, based on the extracted image, a delta file; and transmitting the accessed delta file to a second remote computing device.

Abstract: Disclosed embodiments relate to perform operations for receiving and integrating a delta file in a vehicle. Operations may include receiving, at an Electronic Control Unit (ECU) in the vehicle, a delta file, the delta file comprising a plurality of deltas corresponding to a software update for software on the ECU and startup code for executing the delta file in the ECU; executing the delta file, based on the startup code, in the ECU; and updating memory addresses in the ECU to correspond to the plurality of deltas from the delta file.

Abstract: Disclosed embodiments relate to automatically providing updates to at least one vehicle. Operations may include receiving, at a server remote from the at least one vehicle, Electronic Control Unit (ECU) activity data from the at least one vehicle, the ECU activity data corresponding to actual operation of the ECU in the at least one vehicle; determining, at the server and based on the ECU activity data, a software vulnerability affecting the at least one vehicle, the software vulnerability being determined based on a deviation between the received ECU activity data and expected ECU activity data; identifying, at the server, an ECU software update based on the determined software vulnerability; and sending, from the server, a delta file configured to update software on the ECU with a software update corresponding to the identified ECU software update.

Abstract: Disclosed herein are techniques for analyzing control-flow integrity based on functional line-of-code behavior and relation models. Techniques include receiving data based on runtime operations of a controller; constructing a line-of-code behavior and relation model representing execution of functions on the controller based on the received data; constructing, based on the line-of-code behavioral and relation model, a dynamic control flow integrity model configured for the controller to enforce in real-time; and deploying the dynamic control flow integrity model to the controller.

Abstract: Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring, in the vehicle, data representing real-time processing activity of the ECU; accessing, in the vehicle, historical data relating to processing activity of the ECU, the historical data representing expected processing activity of the ECU; comparing, in the vehicle, the real-time processing activity data with the historical data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.

Abstract: Disclosed herein are techniques for identifying software dependencies based on functional line-of-code behavior and relation models. Techniques include accessing a first line-of-code behavior and relation model representing execution of functions of a first portion of executable code, the first portion of executable code being associated with a first symbol; detecting a change to the first portion of executable code; constructing, based on the changed first portion of executable code, a second line-of-code behavior and relation model representing execution of functions of the changed first portion of executable code; determining, based on the constructed second model, a dependency between (i) the changed first portion of executable code or the first symbol and (ii) a second symbol; and generating, based on the determined difference, a report identifying the dependency.

Abstract: Disclosed herein are techniques for identifying sources of software-based malfunctions. Techniques include identifying a potential software malfunction in a system, the system having multiple code sets associated with a plurality of different software sources; accessing a line-of-code behavior and relation model representing execution of functions of the code sets; identifying, based on the line-of-code behavior and relation model, a code set determined to have the potential to cause, a least in part, the potential software malfunction; and determining a source identifier of the identified code set.