Abstract:
In one embodiment, a device sends collision avoidance safety messages to prevent potential collisions between vehicles and the portable electronic device. The device determines whether a current or predicted future location of the device intersects an action zone. An action zone corresponds to a geographic area in which a potential collision may occur between a vehicle and the device. The device adjusts a broadcast rate for the collision avoidance safety messages based on whether the device determines that the current or predicted future location of the device intersects an action zone.
Abstract:
In one embodiment, a first device in a network receives information regarding one or more nodes in the network. The first device determines a property of the one or more nodes based on the received information. The first device determines a degree of trustworthiness of the one or more nodes based on the received information. The first device attests to the determined property and degree of trustworthiness of the one or more nodes to a verification device. The verification device is configured to verify the attested property and degree of trustworthiness.
Abstract:
Apparatus, methods and logic for vehicles to determine vehicle to vehicle (V2V) safety message transmission rates for transmitting V2V safety messages based on how frequently the vehicles actually need to exchange safety messages, including factors such as vehicle velocities, distances among vehicles, and on how quickly the inter-vehicle distances are closing up. The determined V2V safety message transmission rates are selectively dynamically adjusted in accordance with detected significant changes in one or more of the inter-vehicle distances or inter-vehicle speeds. To avoid needless frequent changes to the transmission rate, statistical modeling techniques including hypothesis testing and sequential change detection are selectively used to more accurately detect significant changes in inter-vehicle distances or inter-vehicle speeds that warrant a change to the message transmission rate.
Abstract:
The trustworthiness of vehicle-to-vehicle (V2V) messages received from one or more associated vehicles in the vicinity of a subject vehicle is determined autonomously by a false signal detection system of the subject vehicle. Physical evidence relating to the associated vehicles is collected, and a statistical model is used to perform an analysis of the collected data. A V2V message is received by the system from a first one of the associated vehicles and a trustworthiness level of the message is determined in accordance with a correlation between the received V2V message and the result of the analyzed physical data relating to the first associated vehicle. The correlation may be a comparison of data contained in the received V2V message relative to a result of a stochastic analysis of the physical data. The received V2V message may be any V2V safety message including Emergency Electronic Brake Light (EEBL) messages.
Abstract:
In one embodiment, a device in a network joins a fog-based malware defense cluster comprising one or more peer devices. The device and each peer device in the cluster are configured to execute a different set of local malware scanners. The device receives a file flagged as suspicious by a node in the network associated with the device. The device determines whether the local malware scanners of the device are able to scan the file. The device sends an assessment request to one or more of the peer devices in the malware defense cluster, in response to determining that the local malware scanners of the device are unable to scan the file.
Abstract:
In an example embodiment herein, there is provided methods and a system for cloud-assisted threat defense for connected vehicles. A vehicle suitably includes an on-board computer system for operating and/or controlling various systems on the vehicle. The on-board computer system suitably operates in connection with or includes an on-board threat defense module for detecting and protecting against malware attacks and other security threats to the vehicle. In an example embodiment, a cloud-based security component or security cloud assists with the detection and protection against security threats and malware attacks to the vehicle while minimizing the processing load and memory requirements for the on-board threat defense module.
Abstract:
Controlled startup of devices is based on dynamic statistical predictions. Timely startup of onboard associated vehicle devices is based on dynamic statistical predictions and driver proximity to the vehicle. An apparatus for timely startup includes an interface operatively coupled with a power consuming device and control logic coupled with the interface. The control logic is operable in a first mode to perform processing for determining a presence of a first condition of the vehicle, and to selectively activate the power consuming device of the vehicle, via the interface, responsive to determining the presence of the first condition. The control logic is operable in a second mode to suspend, via the interface, the processing for determining the presence of the first condition of the vehicle. The control logic selectively transitions between the first and second modes in accordance with a stochastic modeling of the presence of the first condition over time.
Abstract:
In one embodiment, a first device in a network receives information regarding one or more nodes in the network. The first device determines a property of the one or more nodes based on the received information. The first device determines a degree of trustworthiness of the one or more nodes based on the received information. The first device attests to the determined property and degree of trustworthiness of the one or more nodes to a verification device. The verification device is configured to verify the attested property and degree of trustworthiness.
Abstract:
In one embodiment, a first device in a network receives information regarding one or more nodes in the network. The first device determines a property of the one or more nodes based on the received information. The first device determines a degree of trustworthiness of the one or more nodes based on the received information. The first device attests to the determined property and degree of trustworthiness of the one or more nodes to a verification device. The verification device is configured to verify the attested property and degree of trustworthiness.
Abstract:
Controlled startup of devices is based on dynamic statistical predictions. Timely startup of onboard associated vehicle devices is based on dynamic statistical predictions and driver proximity to the vehicle. An apparatus for timely startup includes an interface operatively coupled with a power consuming device and control logic coupled with the interface. The control logic is operable in a first mode to perform processing for determining a presence of a first condition of the vehicle, and to selectively activate the power consuming device of the vehicle, via the interface, responsive to determining the presence of the first condition. The control logic is operable in a second mode to suspend, via the interface, the processing for determining the presence of the first condition of the vehicle. The control logic selectively transitions between the first and second modes in accordance with a stochastic modeling of the presence of the first condition over time.