An immense volume of data is needed to drive Autonomous Vehicles. How that data is acquired, verified and kept secure is what will keep us safe on the road in the coming decades.

As the future of autonomous vehicles sharing the roads with traditional cars becomes a reality, the primary challenge to trust and uptake of these new technologies is clearly safety. Not just the safety of passengers in the driverless cars, but that of the people in traditional vehicles alongside them.

With all the concerns around data security and compromises that continue to make headlines, how will consumers trust that the data flow driving their autonomous vehicle to work is secure?

1996: the year of the first autonomous vehicles

While most consider autonomous vehicles as new and untested in the real world, we should understand that safety has always been a primary concern since Caterpillar introduced its first basic autonomous truck over 20 years ago.

Yes, the coding and systems controlling autonomous vehicles have grown ever more complex since those days. But the data feeding the vehicle to help it “see” the road ahead, behind and beside itself remains an essential component to driver, passenger and pedestrian safety.

Different roads to securing vehicle data

As Bernd Fasternath, leader of the Cities Strategic Projects group at HERE Technologies states, “You can look at security from a few different angles. You can secure the communication channels, you can secure the data as trustworthy from different sources.”

It’s the verification process of data from multiple sources that provides the assurance that the autonomous vehicle makes the right driving decisions with the precision, speed and safety needed.

Verified safety in milliseconds

Take this example: if a specific vehicle has a defect in its Automatic Brake System and continually senses slippery road conditions, that flawed information shouldn’t be shared with other vehicles. Clearly, if those vehicles adjust their driving solely based on flawed data, it could create a problem for everyone on the road. As Bernd explains, “You can already avoid this by combining a few data sources with one another to make sure that the data is true.”

While systems start with data shared by a specific vehicle, they verify that data by checking it against many data sources: other sensors and analytics on that vehicle, other vehicles on the road and the cloud. It’s this multi-source stream of data and verification that ensures autonomous vehicles are acting on good information as they drive.

Bernd notes that “Only after the system verifies the information will it be shared, and all of this verification can happen in milliseconds.”

In the end, the safety of consumers living in a world where multiple levels of autonomous technology share the roads depends on securing and verifying the data that drives the driving decisions. As Bernd explains, “It’s about risk mitigation. The question is in how systems exercise risk mitigation at every single step, and at what point do they trust?”