Patents by Inventor Wendong CHENG

Wendong CHENG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method for detecting CAN bus intrusion of vehicle-mounted network based on GMM-HMM and system
    Patent number: 11985005
    Abstract: The present disclosure provides a method for detecting controller area network (CAN) bus intrusion of a vehicle-mounted network based on a Gaussian mixture model-hidden Markov model (GMM-HMM), including the following steps: obtaining a normal packet of a CAN bus of a vehicle-mounted network, and counting cycles of all packets of each CAN ID based on a time sequence, that is, a time difference between two frames of packets of a same CAN ID, to form a cycle sequence as an input of an algorithm; dividing the cycle sequence of each CAN ID into a fixed length based on the algorithm, and then training a GMM-HMM for each CAN ID to obtain a likelihood probability of a normal cycle sequence; and further counting a cycle sequence of each CAN ID for a tested packet sequence, calculating, after the cycle sequence is input a model, a likelihood probability of generating the sequence, and determining whether the packet sequence is abnormal by comparing the likelihood probability with a threshold of the likelihood probabili
    Type: Grant
    Filed: July 22, 2022
    Date of Patent: May 14, 2024
    Assignees: CHINA AUTOMOTIVE INNOVATION CO., LTD, SHANGHAI UNI-SENTRY INTELLIGENT TECHNOLOGY CO., LTD., EAST CHINA NORMAL UNIVERSITY
    Inventors: Heng Hu, Hongxing Hu, Wendong Cheng, Huibin Huang, Tao Yu, Hong Liu
  • METHOD FOR DETECTING CAN BUS INTRUSION OF VEHICLE-MOUNTED NETWORK BASED ON GMM-HMM AND SYSTEM
    Publication number: 20230137489
    Abstract: The present disclosure provides a method for detecting controller area network (CAN) bus intrusion of a vehicle-mounted network based on a Gaussian mixture model-hidden Markov model (GMM-HMM), including the following steps: obtaining a normal packet of a CAN bus of a vehicle-mounted network, and counting cycles of all packets of each CAN ID based on a time sequence, that is, a time difference between two frames of packets of a same CAN ID, to form a cycle sequence as an input of an algorithm; dividing the cycle sequence of each CAN ID into a fixed length based on the algorithm, and then training a GMM-HMM for each CAN ID to obtain a likelihood probability of a normal cycle sequence; and further counting a cycle sequence of each CAN ID for a tested packet sequence, calculating, after the cycle sequence is input a model, a likelihood probability of generating the sequence, and determining whether the packet sequence is abnormal by comparing the likelihood probability with a threshold of the likelihood probabili
    Type: Application
    Filed: July 22, 2022
    Publication date: May 4, 2023
    Inventors: Heng HU, Hongxing HU, Wendong CHENG, Huibin HUANG, Tao YU, Hong LIU