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Internet of Vehicles (IoV), Intelligent Transport Systems and Cybersecurity

Published: November 2025

The development of Intelligent Transport Systems (ITS) and the Internet of Vehicles (IoV) leads to a networking of vehicles and traffic infrastructures that optimizes traffic flow and increases road safety. Through the integration of technologies such as AI, blockchain, and IoT, vehicles can communicate in real time with traffic lights and other traffic elements, leading to a reduction in congestion and a decrease in environmental impact. Security mechanisms based on blockchain technology and machine learning secure data transmission and protect against cyberattacks. In addition, big data and machine learning are used to predict traffic flows and improve accident prevention techniques. With the further development of 5G and soon 6G networks, communication between vehicles (V2X) and traffic infrastructure will be further improved, contributing to a more efficient and safer transport system.

Guiding questions

  • How can data transmission and cybersecurity in IoV and intelligent transportation systems be optimally secured?
  • What infrastructure is required to ensure smooth and secure communication between vehicles and traffic infrastructure in Thuringia?
  • How can environmentally friendly transport solutions, such as e-vehicles and micro-mobility, be promoted through intelligent transport systems?
  • What measures are necessary to optimize traffic flows in real time while ensuring data protection?

Challenges

The increasing networking and digitalization in traffic bring new security requirements. Cybersecurity mechanisms must be developed to effectively protect IoT environments and vehicle networks from attacks. The detection and defense against cyberattacks, such as DDoS and wormhole attacks, require new methods based on machine learning and blockchain technology. At the same time, the expansion of 5G and future 6G infrastructures, real-time communication, and data processing place high demands on the technological infrastructure. The collection and use of large amounts of data for traffic forecasts and accident analyses must also be designed in a data protection-compliant and efficient manner.

Concrete examples

  • Intelligent traffic light control: e.g., adjusting traffic light phases to traffic volume
  • Collision warning systems for accident prevention: Real-time warnings of approaching vehicles and obstacles

Foresight Report

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Reference

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Reference

Michel Reichardt

Michel Reichardt Project Manager Strategic Foresight

Christoph Grollman

Christoph Grollman Project Manager Strategic Foresight

Dr. Sophia Gänßle

Dr. Sophia Gänßle Project Manager Data Science Strategic Foresight

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