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Development of AI-Powered Vehicle Cybersecurity Platform with Real-Time Monitoring and Threat Prevention
  1. case
  2. Development of AI-Powered Vehicle Cybersecurity Platform with Real-Time Monitoring and Threat Prevention

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Development of AI-Powered Vehicle Cybersecurity Platform with Real-Time Monitoring and Threat Prevention

nix-united.com
Automotive
Security
Information technology

Increasing Cybersecurity Threats in Connected Vehicles

Rapid growth of cyber vulnerabilities in internet-connected vehicles outpaces traditional security standards. Existing solutions lack real-time monitoring capabilities, scalability, and adaptive threat detection mechanisms for CAN bus networks. Organizations require cost-effective protection for both legacy vehicles without embedded security systems and modern vehicles needing additional threat detection layers.

About the Client

Provider of AI/ML-based cybersecurity solutions for connected vehicles, offering intrusion detection and prevention systems for automotive manufacturers and fleet operators.

Objectives for vSentry Platform Development

  • Develop a scalable web application for real-time vehicle data monitoring and threat detection
  • Implement microservice architecture to handle high-volume CAN bus data streams
  • Create AI-powered anomaly detection system using machine learning models
  • Establish secure data encryption processes for vehicle communication networks
  • Provide comprehensive admin tools for error analysis and system configuration

Core System Functionalities

  • CAN bus message decoding from multiple vehicle brands
  • Real-time error handling and anomaly detection dashboard
  • AI engine for baseline behavior modeling and cyberattack identification
  • Cloud data aggregation with TimescaleDB storage
  • Admin panel for statistics visualization and system configuration
  • Third-party system training module for error detection
  • Daily statistics aggregation with filtering capabilities

Technology Stack Requirements

Node.js
React
PostgreSQL
InfluxDB
Apache Kafka
Redis
Kubernetes
Docker
WebSocket
Redux

System Integration Requirements

  • CAN bus vehicle communication systems
  • Cloud storage infrastructure
  • Third-party machine learning frameworks
  • Vehicle telemetry data acquisition modules
  • Security information and event management (SIEM) systems

Non-Functional Requirements

  • High scalability for handling thousands of concurrent vehicle connections
  • Real-time processing with sub-second latency
  • Military-grade data encryption (AES-256)
  • 99.99% system availability with failover mechanisms
  • Compliance with automotive cybersecurity standards (ISO/SAE 21434)
  • Horizontal scaling of microservices architecture

Expected Business Impact

Enables automotive manufacturers and fleet operators to reduce warranty costs by 30-40% through proactive threat detection, minimize vehicle downtime by 25%, and decrease total cost of ownership while maintaining compliance with evolving cybersecurity regulations. Provides real-time vehicle insights for performance optimization and reduces false-positive alerts through AI-powered anomaly detection.

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