CAN Bus Anomaly Detection

Machine learning-based detection of abnormal CAN bus network traffic and behavior
Cybercriminals have more tools, time, finances, and technologies at their disposal than ever before. Focused attacks on high-value targets are growing sharply. At the same time, the increasing dependence of connected vehicles on widely interconnected online systems introduces more attack vectors that attract hacker attention.To achieve critical-modules protection, solutions against cyberattacks on connected vehicles require these major components:

Up-to-Date Threat Intelligence
  • Real-time threat sourcing and update ability
  • Cloud-based big-data analysis and correlation on generating threat knowledge
  • Continuous service guarantee
Pre-Build Solution
Risk Assessment

  • A best-fit solution to protect connected vehicles, according to Auto-ISAC and NHTSA
  • A built-in solution to be able to collect and detect critical modules’ current health and risk status
  • Ability to detect critical modules’ abnormal condition in the system, files, and network connection
  • Ability to detect system vulnerability over time


System Protection

  • A built-in solution to perform threat prevention and mitigation for critical modules
  • A method to deter cyberattacks, such as an intrusion prevention system (IPS)
  • A method to protect system integrity, such as using an approved list for files
Security Visibility
  • A dashboard and management console to have real-time security visibility for the immediate mitigation plan and action
  • Ability to integrate with another back-end system so as to have a single console for the whole management function, including device management, device life cycle management, and security management
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