Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to detect attacks in V2X networks. An example apparatus includes a challenge handler to (a) transmit a first challenge packet to a first vehicle to request a transmission of a first response, (b) instruct a second challenge packet to be transmitted to a second vehicle to request a transmission of a second response, (c) increment a first counter when the first response is not obtained, (d) increment a second counter when the second response is not obtained, and (e) after repeating (a)-(d), determine that the first and second vehicles are phantom vehicles associated with an attacker with a half-duplex radio when at least one of the first or second counters satisfy a threshold, and a network interface to instruct a third vehicle associated with the V2X network to ignore future messages from the phantom vehicles based on the determination.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to validate data communicated by a vehicle. An example apparatus an anomaly detector to, in response to data communicated by a vehicle, at least one of compare an estimated speed with a reported speed or compare a location of the vehicle with a reported location. The apparatus including the anomaly detector further to generate an indication of the vehicle in response to the comparison. The apparatus further includes a notifier to discard data sent by the vehicle and notify surrounding vehicles of the data communicated by the vehicle.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to validate data communicated by a vehicle. An example apparatus an anomaly detector to, in response to data communicated by a vehicle, at least one of compare an estimated speed with a reported speed or compare a location of the vehicle with a reported location. The apparatus including the anomaly detector further to generate an indication of the vehicle in response to the comparison. The apparatus further includes a notifier to discard data sent by the vehicle and notify surrounding vehicles of the data communicated by the vehicle.

Abstract: Systems, apparatuses, methods, and computer-readable media are provided for load partitioning in distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective load partitions. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of respective computational and link parameters of the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: Systems, apparatuses, methods, and computer-readable media, are provided for distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective training datasets, and a master combines the outputs of the ML computations obtained from individual heterogeneous compute nodes. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of network conditions and operational constraints experienced by the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to detect attacks in V2X networks. An example apparatus includes a challenge handler to (a) transmit a first challenge packet to a first vehicle to request a transmission of a first response, (b) instruct a second challenge packet to be transmitted to a second vehicle to request a transmission of a second response, (c) increment a first counter when the first response is not obtained, (d) increment a second counter when the second response is not obtained, and (e) after repeating (a)-(d), determine that the first and second vehicles are phantom vehicles associated with an attacker with a half-duplex radio when at least one of the first or second counters satisfy a threshold, and a network interface to instruct a third vehicle associated with the V2X network to ignore future messages from the phantom vehicles based on the determination.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to detect attacks in V2X networks. An example apparatus includes a challenge handler to (a) transmit a first challenge packet to a first vehicle to request a transmission of a first response, (b) instruct a second challenge packet to be transmitted to a second vehicle to request a transmission of a second response, (c) increment a first counter when the first response is not obtained, (d) increment a second counter when the second response is not obtained, and (e) after repeating (a)-(d), determine that the first and second vehicles are phantom vehicles associated with an attacker with a half-duplex radio when at least one of the first or second counters satisfy a threshold, and a network interface to instruct a third vehicle associated with the V2X network to ignore future messages from the phantom vehicles based on the determination.

Abstract: Systems, apparatuses, methods, and computer-readable media, are provided for distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective training datasets, and a master combines the outputs of the ML computations obtained from individual heterogeneous compute nodes. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of network conditions and operational constraints experienced by the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to validate data communicated by a vehicle. An example apparatus an anomaly detector to, in response to data communicated by a vehicle, at least one of compare an estimated speed with a reported speed or compare a location of the vehicle with a reported location. The apparatus including the anomaly detector further to generate an indication of the vehicle in response to the comparison. The apparatus further includes a notifier to discard data sent by the vehicle and notify surrounding vehicles of the data communicated by the vehicle.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to validate data communicated by a vehicle. An example apparatus an anomaly detector to, in response to data communicated by a vehicle, at least one of compare an estimated speed with a reported speed or compare a location of the vehicle with a reported location. The apparatus including the anomaly detector further to generate an indication of the vehicle in response to the comparison. The apparatus further includes a notifier to discard data sent by the vehicle and notify surrounding vehicles of the data communicated by the vehicle.

Abstract: Systems, apparatuses, methods, and computer-readable media are provided for load partitioning in distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective load partitions. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of respective computational and link parameters of the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to detect attacks in V2X networks. An example apparatus includes a challenge handler to (a) transmit a first challenge packet to a first vehicle to request a transmission of a first response, (b) instruct a second challenge packet to be transmitted to a second vehicle to request a transmission of a second response, (c) increment a first counter when the first response is not obtained, (d) increment a second counter when the second response is not obtained, and (e) after repeating (a)-(d), determine that the first and second vehicles are phantom vehicles associated with an attacker with a half-duplex radio when at least one of the first or second counters satisfy a threshold, and a network interface to instruct a third vehicle associated with the V2X network to ignore future messages from the phantom vehicles based on the determination.

Abstract: Systems, apparatuses, methods, and computer-readable media, are provided for distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective training datasets, and a master combines the outputs of the ML computations obtained from individual heterogeneous compute nodes. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of network conditions and operational constraints experienced by the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to validate data communicated by a vehicle. An example apparatus an anomaly detector to, in response to data communicated by a vehicle, at least one of compare an estimated speed with a reported speed or compare a location of the vehicle with a reported location. The apparatus including the anomaly detector further to generate an indication of the vehicle in response to the comparison. The apparatus further includes a notifier to discard data sent by the vehicle and notify surrounding vehicles of the data communicated by the vehicle.