Blockchain for connected and self-driving cars (Part 24)

Welcome to the 24th part of the 100 part series on Blockchain.

The future belongs to cars that are connected to the internet. They can communicate via IoT devices and enable the vehicle to vehicle communication. Through IoT devices, connected cars can connect to traffic, weather, location, and travel conditions. But there is still a time when these connected cars will be available for mass adoption, as many critical issues still need to be addressed before making them available for the masses. One of the biggest challenges that bother these connected cars is security. The more they are connected to IoT devices, the more they become susceptible to cyber attacks.

Enter Blockchain. Blockchain has the ability to safeguard the information exchange through IoT devices, thus making them resistant against any attack by fraudsters. Let’s see how Blockchain will work for connected cars:

Edge, and Cloud computing in connected cars

In a connected and self-driving car, there are smart IoT sensors that can collect information on everything from location, weather, damaged roads, and damaged bridges, to parking availability, congestion, and even about the breakdown of the vehicle.

Edge computing: Let’s understand edge computing by taking an example of an autonomous or self-driving car running on a highway. After seeing an obstacle, the car has to apply a brake instantaneously to avoid an accident. Here, sending the data back and forth from the car to the servers on the cloud either directly or via a gateway, in order to be processed and then waiting for cloud triggering to apply brakes can create latency in the response time, and the consequences can be dire where even a millisecond lag can be the difference between life and death. Here comes the need for edge computing with integrated artificial intelligence (AI) tools. With the help of Edge Computing, the live video can be processed closer to the IoT sensor that captured it; in other words, computation takes place at the edge of a device’s network. Because of this, processing will be fast, and real-time action can be taken without any adverse effects. For this, the edge server may be present in the autonomous car itself, or the data may be sent from the car to the geographically distributed nearest edge server, which processes the data and the processed results are notified directly to the vehicles, thus, improving the real-time performance.

Edge computing

Edge computing has many other use cases too. For instance, in the case of rash driving, data collected from the car’s sensors, accelerometer and gyrometer can be computed at the same place where it is gathered and generates the corresponding required alerts to maintain the safe driving standards. Similarly, on-board diagnostics tools and interfaces in the car help in detecting real-time problems within the car and generate the required alerts for the drivers. Data received from the onboard diagnostic tools can be continuously monitored with the help of Edge Computing, and any failure or risk can be predicted before actual damage.

Through edge computing, every connected vehicle can become a repository of data. This data can be used by third parties to offer services such as route guidance for travelers, ride-sharing, and providing information that can guide traffic flow control by road authorities.

Cloud computing: Edge computing is not the replacement for the cloud; it helps to offload some of the resource-intensive work from the cloud. With edge computing, data sent to the cloud could be minimized. It can process and analyze that data at the edge, which requires a quick response, and other data is transferred to the cloud via the internet. The cloud stores the IoT data and processes it to get real insights into the vehicle, geographical locations, consumer usage patterns, and environmental changes. For instance, smart cameras at the edge can detect movement in real-time, and a nearby edge server can process the data and determine whether the movement poses a threat. And the cloud can collect and analyze IoT data over the long term to help businesses understand environmental patterns.

Challenges with edge computing: Undoubtedly, edge computing is an innovative computing method, but it faces a series of security risks, as it does not always ensure the protection of edge servers, fog servers, and IoT devices as they are vulnerable to cyberattacks. There have been a number of incidents in which attackers hijacked IoT devices within an edge computing infrastructure. Security breaches can compromise sensitive data and put trade secrets or other corporate information at risk. They can also interrupt or even halt business operations entirely. The hackers may even turn an autonomous vehicle into a dangerous weapon by taking its control.

Blockchain-enabled Edge computing

A permissioned Blockchain network must be created to prevent hackers from hijacking edge servers and accessing or manipulating sensitive information. Each edge server together with the IoT devices connected to it will be the nodes that form the local network. The IoT sensors will generate data and send it to their assigned edge server. The edge server will then verify the data and broadcast it to the other edge servers of the network. After achieving the consensus from the network, the verified data is uploaded as a transaction on the Blockchain. Communication between IoT devices, between devices and the edge server, or between edge servers are recorded as transactions and stored on the Blockchain. Edge servers process real-time requests, and the processed data is also stored as a transaction on the Blockchain.

Blockchain-enabled Edge computing

Each node has a unique ID and a pair of private and public keys. Whenever a node sends data to the edge node, it signs the data with its private key. Other nodes in the network can verify the identity of a sender node by its public key. Thus, it makes hacking of edge servers and IoT devices difficult and secures the data received from devices. It is essential to secure the IoT and edge server’s data at all times because any hacking activity on this data can even cost lives. Therefore, uploading data derived from IoT devices on Blockchain is very critical for making it secure and resistant to hacking.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity

As the name suggests, vehicle-to-vehicle connectivity allows connected vehicles to communicate with each other on the road by sharing data about speed, road conditions, etc. This technology provides great promise in reducing vehicle accidents and traffic congestion on the roads. There’s also vehicle-to-infrastructure (V2I) communication, which allows cars to connect with various road infrastructures like traffic lights, road signs, lane markings, construction zones, and school zones. This would help your car find the safest and most efficient route to your destination in real-time.

But if the malicious actors hack the devices responsible for V2V or V2I connectivity, they may mislead the information and create chaos on the road. Further, data falsification attack is another security issue in connected cars where vehicles rely on information received from other vehicles. To avoid any such incidents, Blockchain can provide the required safety and security to the data so that hackers can not view or alter the data collected by these devices. In case any IoT device is compromised by the hackers, the respective authorities and other nodes that are part of the Blockchain may be able to identify and take immediate actions against that compromised IoT device. Similarly, for self-driving cars, data hacking can be disastrous. In these cars as well, Blockchain can provide the much-needed safety net to make its data secure.

Responsible driving behavior

Blockchain technology may also ensure customer safety during cab riding. In the Blockchain network, the vehicles need to be registered and will be considered as nodes which are further divided into validating/miner nodes depending upon their service criteria. The authenticity of a new vehicle or IoT device joining the network is verified in order to avoid network failures. The vehicle number, current and previous vehicle ratings, along with the data captured by IoT devices are stored on the Blockchain network. Therefore, even if the hacker or cab driver hacks one or more IoT objects to gain their benefits, the nodes or vehicles present in the network will be aware of the information registered under that compromised IoT device. Thus, any compromise in any IoT device would be recorded on the Blockchain. Therefore, Blockchain technology ensures the security and traceability of IoT devices or a vehicle’s legal or illegal activity information.


The vehicle infotainment system provides an audio-video experience for car riders. Car owner needs to subscribe to these infotainment services provided by various providers. Blockchain can provide a great application in this scenario as well. Blockchain can enable vehicle owners to make in-car payments for infotainment services like movies, apps, and other services based on predefined contracts.


Imagine a scenario where you have to pay for your car insurance based on how much you actually use your car rather than on a set of predefined insurance policy conditions. Blockchain technology can help insurance companies to create personalized vehicle insurance contracts based on actual driver behavior. A connected car can capture information on driver location, drive duration, mileage of the vehicle, vehicle speed, and other information like the accident history of the car. And Blockchain provides a foolproof means for collecting this data and delivering it in a secure and unalterable manner to the insurance companies. This will make the cost of insurance premiums fairer, and you will pay as you drive or how you drive. Additionally, through smart contracts, automatic payment of insurance premiums can be directly executed.

Blockchain and IoT for automatic repairing and payment

Another interesting thing that Blockchain and IoT can do is automatic order placing to repair any part of the car and then release automatic payment for the services rendered. In such a system, sensors in the car would first detect the need to repair a particular part. After this, they would contact nearby suppliers for replacement parts, followed by fixing an appointment with a technician for service and repairs. And once repairing is done, smart contracts will get executed, which will automatically process the respective payment for the services rendered.

Smart car parking and payment

Smart parking is another area that can be targeted through the integration of blockchain and IoT. In this system, IoT sensors will first locate a vacant space in the parking lot. And once the car is parked, they will even calculate the duration for which the car remains parked there. Additionally, during the payment phase, the smart contract will get executed, and automated payouts will be done based on the parking time calculated by the sensors.

Other related articles:


Damianou, A., Angelopoulos, C. M., & Katos, V. (2019, May). An architecture for blockchain over edge-enabled IoT for smart circular cities. In 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS) (pp. 465–472). IEEE.

Hosono, K., Maki, A., Watanabe, Y., Takada, H., & Sato, K. (2022). Efficient Access Method for Multi-access Edge Servers in Dynamic Map Systems. International Journal of Intelligent Transportation Systems Research, 1–14.

Jiao, Y., Wang, P., Niyato, D., & Xiong, Z. (2018, May). Social welfare maximization auction in edge computing resource allocation for mobile blockchain. In 2018 IEEE international conference on communications (ICC) (pp. 1–6). IEEE.

Nyamtiga, B. W., Sicato, J. C. S., Rathore, S., Sung, Y., & Park, J. H. (2019). Blockchain-based secure storage management with edge computing for IoT. Electronics, 8(8), 828.

Wu, Y., Dai, H. N., & Wang, H. (2020). Convergence of blockchain and edge computing for secure and scalable IIoT critical infrastructures in industry 4.0. IEEE Internet of Things Journal, 8(4), 2300–2317.

Thanks for reading!



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