Intel Corporation

Huawei Technologies Co., Limited

Apple Inc.

Future Wei Technologies, Inc.

Qian Wang

Manoj R Sastry

Marcio Rogerio Juliato

Shabbir Ahmed

Christopher N Gutierrez

Vuk Lesi

Liuyang L Yang

Xingyu Jiang

Xiruo Liu

Wen-Ling Huang

Eduardo Alban

Saiveena Kesaraju

Christopher Hall

Ivan Simoes Gaspar

Yuejian Xie

Rath Vannithamby

Markus Dominik Mueck

Kathiravetpillai Sivanesan

Wei Yu Chen

Daniel R Kurz

Dave A Cavalcanti

Vallabhajosyula S Somayazulu

Javier Perez-Ramirez

Leonardo Gomes Baltar

Ning Yang

Da Qi Ren

Thomas Gebauer

Lixia Yang

Shiwen Hu

Muhammad Ahmed Riaz

Dewey H Lee

Yongbin Zhou

Michael Chow

Marcio Juliato

A computing node to implement a management entity in a CP-based network. The node including processing circuitry configured to encode an inquiry message requesting information on CPS capabilities. Response messages are received from a set of sensing nodes of a plurality of sensing nodes in response to the inquiry message. The response messages include the information on the CPS capabilities of the set of sensing nodes. A notification message indicating selecting of a sensing node as a sensing coordinator is encoded for transmission. Sensed data received in a broadcast message from the sensing coordinator is decoded. The sensed data including data associated with one or more non-V2X capable sensing nodes.

Occupancy grid map computation, V2X complementary sensing, and coordination of cooperative perception data transmission in wireless networks

Branch prediction techniques for pipelined microprocessors are disclosed. A microprocessor for branch predictor selection includes a fetch stage configured to retrieve instructions from a memory. A buffer is configured to store instructions retrieved by the fetch stage, and one or more pipelined stages configured to execute the instructions stored in the buffer. The branch predictor, communicatively coupled to the buffer and the one or more pipelined stages, is configured to select a branch target predictor from a set of branch target predictors. Each of the branch target predictors comprise a trained model associated with a previously executed instruction to identify a target branch path for the instruction currently being executed based on the selected branch target predictor.

Apparatus and method for branch prediction using machine learning with new learning models

Systems, apparatuses and methods may provide for technology that detects one or more non-compliant nodes with respect to a timing schedule, detects one or more compliant nodes with respect to the timing schedule, and identifies a malicious node based on positions of the one or more non-compliant nodes and the one or more compliant nodes in a network topography. The non-compliant node(s) and the compliant node(s) may be detected based on post-synchronization messages, historical attribute data and/or plane diversity data.

Attacker localization based on tracking anomaly propagation in time-sensitive networking

The disclosure relates to technology for bulk initialization of memory in a computer system. The computer system comprises a processor core comprising a load store unit and a last level cache in communication with the processor core. The last level cache is configured to receive bulk store operations from the load store unit. Each bulk store operation includes a physical address in the memory to be initialized. The last level cache is configured to send multiple write transactions to the memory for each bulk store operation to perform a bulk initialization of the memory for each bulk store operation. The last level cache is configured to track status of the bulk store operations.

Bulk memory initialization

Techniques for clock manager monitoring for time sensitive networks are described. An apparatus, comprises a clock circuitry to manage a clock for a device, a processing circuitry coupled to the clock circuitry, the processing circuitry to execute instructions to perform operations for a clock manager, the clock manager to receive messages with time information for a network and generate clock manager control information to adjust the clock to a network time for the network, and a detector coupled to the processing circuitry and the clock circuitry, the detector to receive the clock manager control information, generate model control information based on a clock model, compare the clock manager control information with the model control information to generate difference information, and determine whether to generate an alert based on the difference information. Other embodiments are described and claimed.

Clock manager monitoring for time synchronized networks

Systems, apparatuses, and methods to attest to and verify the integrity of cargo during transport by an autonomous vehicle are provided. An autonomous vehicle can discretize parameters associated with transportation of cargo and can generate a keyed hash digest from the discretized parameters. The keyed hash digest can be sent to a stakeholder in the transportation of the cargo to attest to the integrity of the cargo during transport.

Continuous integrity monitoring for autonomous transportation services

Systems, apparatuses, and methods to identify bus-off and masquerade attacks against electronic control units (ECUs) transmitting on a communication bus from behind a gateway coupled to the communication bus are described. The disclosure further describes systems, apparatuses, and methods to mitigate against bus-off attacks made against an ECU coupled to a communication bus through a gateway. Other embodiments are described and claimed.

Post-gateway bus-off attack mitigation

Systems, apparatuses, and methods to establish ground truth for an intrusion detection system in the presence of an attacker electronic control unit transmitting masqueraded messages on a communication bus, such as an in-vehicle network bus, are provided.

Re-training intrusion detection fingerprints in the presence of an attacker

Systems and techniques for malicious request detection in automated resource dispatch are described herein. A request for a resource may be received from a user device. A location may be obtained for delivery of the resource. Sensor data may be retrieved for the location. The sensor data and user profile data may be evaluated to determine if the request is malicious. A disincentivizing message may be generated based on the determination that the request is malicious. In response to receipt of a response to the disincentivizing message, a resource may be dispatched to the location.

Malicious request detection in automated resource dispatch

Time recovery techniques are described. A method comprises receiving messages from the first device by the second device in the first network domain, the messages to comprise time information to synchronize a first clock for the first device and a second clock for the second device to a network time, determining the second clock is to recover the network time for the second device without new messages from the first device, retrieving a first set of timestamps previously stored for events in the first network domain using the network time from the second clock, retrieving a second set of timestamps previously stored for the events in the first network domain using a redundant time from a third clock, where the third clock is not synchronized with the first and second clocks, and recovering the network time using a regression model and the redundant time from the third clock.

Time recovery in a time sensitive network

Systems, apparatuses, and methods to identify an electronic control unit transmitting a message on a communication bus, such as an in-vehicle network bus, are provided. ECUs transmit messages by manipulating voltage on conductive lines of the bus. Observation circuitry can observe voltage signals associated with the transmission at a point on the in-vehicle network bus. A distribution can be generated from densities of the voltage signals. ECUs can be identified and/or fingerprinted based on the distributions.

Lightweight electronic control unit fingerprinting

Techniques to secure a time sensitive network are described. An apparatus may establish a data stream between a first device and a second device in a network domain, the network domain includes a plurality of switching nodes, receive messages from the first device by the second device in the network domain, the messages to comprise time information to synchronize a first clock for the first device and a second clock for the second device to a network time for the network domain, update a correction field for a received message with a residence time and time delay value by the second device, determine whether the updated message is benign or malicious, update the correction field for the updated message with an inference time when the updated message is benign, and prevent relay of the updated message to other devices in the network domain when the updated message is malicious.

Inference models for intrusion detection systems in time sensitive networks

Systems, apparatuses, and methods to identify an electronic control unit transmitting a message on a communication bus, such as an in-vehicle network bus, are provided. ECUs transmit messages by manipulating voltage on conductive lines of the bus. Observation circuitry can observe voltage transitions associated with the transmission at a point on the in-vehicle network bus. A domain bitmap can be generated from the observed voltage transitions. ECUs can be identified and/or fingerprinted based on the domain bitmaps.

One-point relative voltage fingerprinting

Systems, apparatuses, and methods to response to distinguish a ghost target from an actual target based on radar signals is provided. In particular, the disclosure provides an intrusion detection system adapted to receive radar signals and distinguish a potential ghost target from a legitimate target based on a signal to noise ratio of the radar signals and a range to the ghost target and the legitimate target.

Signal-to-noise ratio range consistency check for radar ghost target detection

Logic may implement observation layer intrusion detection systems (IDSs) to combine observations by intrusion detectors and/or other intrusion detection systems. Logic may monitor one or more control units at one or more observation layers of an in-vehicle network, each of the one or more control units to perform a vehicle function. Logic may combine observations of the one or more control units at the one or more observation layers. Logic may determine, based on a combination of the observations, that one or more of the observations represent an intrusion. Logic may determine, based at least on the observations, characteristics of an attack, and to pass the characteristics of the attack information to a forensic logging system to log the attack or pass the characteristics of the attack to a recovery system for informed selection of recovery procedures. Logic may dynamically adjust a threshold for detection of suspicious activity.

Growing community of inventors

Santa Clara, CA, United States of America

Qian Wang