How Cynamics Is Securing the Next Generation of Connected Vehicles

We’re excited to announce that our latest research paper, “Cybersecurity for Connected Vehicle Networks: Leveraging Sampled Network Traffic Beyond the CAN Protocol,” has been accepted for IEEE CSR, one of the leading conferences for cybersecurity research. This recognition highlights Cynamics’ commitment to pushing the boundaries of cybersecurity innovation - especially in the fast-evolving world of connected vehicles.

At Cynamics, we believe the future of mobility must be connected - and secure. As cars evolve into sophisticated, always-connected computers on wheels, they create new opportunities for innovation - but also new opportunities for cyber threats.

Modern vehicles rely on dynamic, high-bandwidth networks that connect dozens of electronic control units (ECUs), sensors, external infrastructure, and cloud services. This advanced connectivity powers incredible features like real-time navigation, autonomous driving, and Vehicle-to-Everything (V2X) communication. But it also means that traditional methods for detecting cyberattacks are no longer enough.

The Problem: Legacy Detection Falls Short

For years, most automotive cybersecurity solutions have focused on monitoring the CAN bus, the simple but vital protocol cars have used to let internal components communicate. While CAN-based monitoring helps catch some attacks, it only covers a small part of the modern vehicle’s true network surface.

Today’s vehicles handle significant amounts of data over high-speed Ethernet, wireless interfaces, and cloud connections. These networks are dynamic - they constantly change with new software updates, traffic patterns, and user behavior. This complexity makes them harder to protect using traditional, static monitoring systems like CAN bus and requires new approaches.

The Cynamics Solution: Smart Sampling for Dynamic Networks

At Cynamics, we’re tackling this problem with a fresh approach: sample-based network anomaly detection for vehicles. Instead of trying to capture and analyze every single packet - which is impractical and intrusive - we analyze small samples of network traffic, less than 1%.

Why does this work so well for connected cars?

Scalable: Sampling reduces the load on vehicle systems, making real-time protection possible even as network speeds and volumes increase.Privacy-Preserving: By focusing on metadata and traffic patterns - not deep packet inspection - we protect sensitive driver data and stay compliant with privacy standards.Dynamic Threat Detection: Sophisticated attacks don’t happen in one step - they involve a series of suspicious behaviors across multiple network layers. Our method detects these unusual patterns, even in dynamic, encrypted, or high-speed environments.Proven in Real Vehicles: We recently validated this approach with a leading automotive manufacturer. The results showed that even with small samples, our system accurately detected a wide range of attack scenarios - and even identified unusual driving behavior that could signal a hijacking attempt.

Securing the Road Ahead

The connected car ecosystem will only become more complex. From autonomous vehicles to smart cities, the need for dynamic, scalable, and privacy-first cybersecurity is clear.

At Cynamics, we’re excited to lead this next phase. By applying our proven, network-based anomaly detection technology to the automotive world, we’re helping manufacturers keep vehicles - and the people inside them - safe from ever-evolving threats.

Want to learn more about how Cynamics is redefining automotive cybersecurity? Contact us or visit our website to see how we can help secure your connected fleet for the road ahead.