Home / Opinion / Technology / AI and Blockchain Will Expand the $1.55T Autonomous Vehicle Market

AI and Blockchain Will Expand the $1.55T Autonomous Vehicle Market

Published
Lisa Gibbons
Published
By Lisa Gibbons
Edited by Samantha Dunn
Key Takeaways
  • The race for the smartest cities in the world is beginning to heat up, and one of the hottest optics is autonomous vehicles.
  • Autonomous vehicles rely on interconnected systems, sensors, and AI-driven decision-making.
  • Nonetheless, there are challenges with using AI as these create an attractive target for hackers.

The global Autonomous Cars Market size was valued at USD 1.55 trillion  in 2022 and is anticipated to register a CAGR of 10.3% from 2023 to 2032, owing to an increased emphasis on vehicle safety and efficiency.

According to Next Move Strategy Consulting, the global autonomous vehicle market  is expected to grow from 16,960 units in 2022 to 125,660 units in 2030.

AI and Autonomous Vehicles

Just last month, Chinese tech giant Baidu won Hong Kong’s first-ever license to test autonomous vehicles, while in fast-paced California, Waymo already has its driverless taxis out on the roads.

The vehicles are geofenced, so they can only operate in specific regions, but their fleet size is growing.

The rise of autonomous vehicles, artificial intelligence, and blockchain technology is opening up a whole new world of efficiency in the automotive sector.

However, these advances bring new vulnerabilities, making robust cybersecurity solutions critical to both protect the customer and make our roads safer.

The Pain Points of AI in Automotive Transformation

Given that driverless cars rely on reliable data and sensors, AI could prove to be a very valuable tool for processing and interpreting this data.

However, AI introduces as many challenges as it solves. The recent push for autonomous driving brings with it the need to ensure the ethical use of data and address the growing cybersecurity threats posed by advanced AI systems.

Charles Dray of Resonance Security emphasizes the importance of thorough preparation,

“AI and blockchain offer incredible potential for automotive security, but they must be implemented with care. A failure to understand legacy systems and existing vulnerabilities could lead to solutions that introduce more problems than they solve.”

Balancing innovation with reliability requires a deep understanding of industry pain points and a commitment to rigorous testing and collaboration.

How AI and Blockchain Prioritize Security

AI excels at analyzing vast datasets in real-time. For instance, it can identify unusual patterns in vehicle communications, signaling unauthorized access or tampering.

“AI can monitor networks for anomalies, analyze data from Bluetooth, sensors, and other inputs, and help vehicles anticipate traffic patterns and hazards. However, robust testing and threat modeling are critical to ensure these systems don’t backfire,” says Dray.

Blockchain technology enhances security by ensuring immutable, tamper-proof communication between vehicles, infrastructure, and service providers.

This is particularly valuable in Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) interactions. As Dray explains, blockchain not only secures communication but also supports transparent investigations by creating an unalterable log of data exchanges.

Security Challenges of Autonomous Vehicles

As Autonomous vehicles use interconnected systems, sensors, and AI-driven decision-making, this connectivity exposes them to significant cybersecurity threats and opens up a whole new window of privacy concerns.

“A compromised vehicle could lead to catastrophic consequences, from personal safety risks to disruption of transportation systems. The primary challenge is securing data integrity while protecting against malicious interference,” notes Lisa Loud, CEO of Secret Network, a privacy-based protocol.

Autonomous vehicles rely on accurate identification of their environments, including pedestrians, other vehicles, and road signs. Providing access to these objects to AI raises a number of questions:

What can the AI see? What data is collected? Where is the data stored? How is it used?

Sensitive data like driving behavior, diagnostics, and even passenger identities are continuously exchanged in real-time. This creates a vast attack surface, ranging from zero-day attacks exploiting unpatched vulnerabilities to adversarial AI inputs that manipulate vehicle sensors.

How To Protect Data Using Confidential Computing

One of the most pressing concerns is processing sensitive data, like driving habits or vehicle diagnostics, without exposing it to potential breaches. Confidential computing  is key to answering this.

According to Loud, “Confidential computing creates secure enclaves within the vehicle’s systems, isolating sensitive data from the broader ecosystem. Even if a breach occurs, the encrypted data remains inaccessible.”

This technology ensures that data remains private during real-time analytics, enabling autonomous systems to make informed decisions without jeopardizing security.

The pairing of AI and confidential computing also unlocks new possibilities for over-the-air (OTA) updates. These updates are essential for keeping autonomous systems current but also present a security risk.

“AI can verify the authenticity of OTA updates, while confidential computing ensures that updates don’t expose the vehicle’s core systems to tampering. This creates a secure, trustworthy ecosystem for innovation,” notes Loud.

Despite their promise, AI and blockchain aren’t silver bullets.

“The current state of technology isn’t advanced enough for full autonomy. These systems should serve as assistive tools to operators, not replacements. Integrating them with legacy systems also requires careful consideration, ” says Dray.

This calls for a collaborative approach, where manufacturers, cybersecurity engineers, and third-party vendors work together to secure these technologies before they are widely deployed.

The Road Ahead

News reports have surfaced on how the Trump team is looking to loosen the rules  around self-driving cars. If more driverless cars enter our daily routines, there is an opportunity to enhance their security at every level using AI and blockchain technologies.

“AI and blockchain don’t just secure vehicles. They create opportunities for safer, more efficient transportation,” says Dray. With continuous advancements and robust security frameworks, the automotive industry is poised to drive into an era where innovation and safety go hand in hand.

Dray points to an exciting future where AI and blockchain combine to tokenize and encrypt critical vehicle data. These technologies can create a safer, more cooperative driving environment by securely sharing information like vehicle speed, location, or driver authorization across systems.

AI will undoubtedly infiltrate our everyday lives more and more. Sharing data to create safer roads is just one of many ways in which AI can be used for good.

Disclaimer: The views, thoughts, and opinions expressed in the article belong solely to the author, and not necessarily to CCN, its management, employees, or affiliates. This content is for informational purposes only and should not be considered professional advice.

Lisa Gibbons

Lisa is a passionate blockchain professional with a love for the metaverse, tourism, education and sustainability. Most recently she founded the Metaverse Tourism Association, designed to bring the leading minds in travel and tech together to collaborate towards a hybrid future. In 2017 she founded Orchardsnearme.com, a platform dedicated to wild food foraging and sustainable food distribution that is a mini tourism project. Lisa has a love for the written word, poetry NFTs and is fascinated by the technology that brings digital assets to life.
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