Why teach cybersecurity using physical systems such as collaborative robots?

Cybersecurity is now a critical issue for businesses, institutions, and industrial infrastructure alike. Yet it is still often taught in highly theoretical ways: abstract network analysis, exercises on virtual machines, or case studies far removed from real-world environments.

In response, new teaching approaches are emerging. Among them, learning cybersecurity through application-based scenarios involving real physical systems, such as collaborative robots, is proving to be a particularly relevant method.

Why is this approach transforming the learning experience? What concrete benefits does it bring to learners? That is what we explore below.

Making cybersecurity tangible and easier to understand

In many academic programs, cybersecurity is introduced through abstract systems such as remote servers, cloud infrastructure, or virtual machines. While these environments are useful, they can sometimes make learning more difficult for beginners.

Using a real, programmable robot changes that perspective entirely.

Instead of working on a simulated computer, learners interact with a connected physical system they can observe, handle, and program. The robot becomes an ideal entry point for understanding that:

• a robot is, first and foremost, a connected computing system
• it runs active network services
• it can be targeted by cyberattacks
• a successful compromise can have physical consequences

This approach makes it much easier to connect cybersecurity concepts with their real-world impact.

Learning cybersecurity through a project-based approach

Another common limitation of traditional teaching is the gap between theory and practice. Learners study concepts without always seeing how to apply them.

That is why some educational solutions, such as those offered by Niryo, take a project-based, hands-on approach.

In this context, learners do more than study cybersecurity. They work directly on a real collaborative robot, such as the Ned2 robot.

For example, they can:

• program robot movements and actions
• create scripts and services
• observe the robot’s network communications
• analyse the system’s exposure points

This kind of immersion helps learners understand that cybersecurity is not limited to protecting computers. It applies to any connected system, including physical machines.

Understanding the real risks of an attack on a robotic system

One of the major advantages of using an educational robot is that it provides a very concrete way to illustrate the consequences of an attack.

When learners secure a robot, they quickly realise that several elements need to be protected:

• data
• network services
• control scripts
• the robot itself

They also discover essential concepts such as:

• active network services (SSH, ports, protocols)
• potential vulnerabilities in connected systems
• possible attack vectors

This approach helps build a systems-level understanding of cybersecurity, where software, networks, and hardware must all be secured together.

Cybersecurity made accessible, even for beginners

Contrary to common belief, cybersecurity is not only for technical experts. When it is taught in a well-structured way, it can be introduced progressively, even to beginner-level learners.

Using a real robot supports this learning process by making concepts more intuitive.

Students gradually learn how to:

• identify system vulnerabilities
• determine what needs to be protected
• understand how network services operate
• implement practical protection measures

In doing so, they build a clear and reusable cybersecurity methodology that can be applied to other technical environments.

Building well-rounded professional skills

Beyond the technical dimension, project-based learning also helps develop essential professional skills.

In a teaching scenario built around a real robot, learners are required to:

• carry out a risk analysis
• implement a security strategy
• monitor and assess the system
• document their technical decisions
• explain their attack and defence logic

This approach fosters autonomy, critical thinking, and the ability to solve complex problems.

In other words, students do not simply learn tools. They develop a genuine cybersecurity mindset.

Understanding the attack / defence dynamic

One of the foundations of cybersecurity is understanding the relationship between attackers and defenders.

An educational robot is an excellent way to illustrate this dynamic. Learners can analyse:

• how a system can be exploited
• which vulnerabilities can be targeted
• which measures can prevent or limit an attack

This helps them understand how cybersecurity works in practice, rather than simply memorising theoretical concepts.

An approach aligned with industrial challenges

In modern industry, cyber-physical systems are becoming increasingly widespread: industrial robots, connected machines, and smart infrastructure.

Cybersecurity must therefore protect hybrid environments that combine IT and physical systems.

Training learners on collaborative robots helps prepare them for that reality.

They come to understand that cybersecurity now applies to:

• traditional IT
• IoT
• industrial systems
• robotics

This broader perspective directly reflects business needs and the challenges of Industry 4.0.

Conclusion

Cybersecurity education is evolving rapidly to keep pace with new technological environments.

The use of physical systems such as collaborative robots now represents a particularly effective teaching approach. It makes cybersecurity:

• more tangible
• easier to understand
• more engaging
• more closely aligned with industrial reality

By integrating real robots into learning pathways, learners do more than study cybersecurity. They practise it in scenarios that closely reflect the professional world.

With our Cybersecurity & Networks Pack, this is exactly the kind of immersive experience that helps train the experts who will secure tomorrow’s cyber-physical systems.