The Rise of Physical AI and Robotics: Why Hardware-Based Security is Non-Negotiable

By Sara Brax

May 7, 2026

Whether you’re a technologist, business leader, or simply curious, physical AI is reshaping how we live, work, and interact with the world. Its potential to augment human capabilities, solve global challenges, and create new industries is why physical AI is dominating conversations today. But how do we secure these systems against cyber threats that could have real-world consequences?

Introduction

As artificial intelligence moves beyond the digital realm and into our physical world, it brings unprecedented opportunities and risks. These systems power everything from autonomous vehicles to smart infrastructure, and they’re no longer just processing data. They’re interacting with environments, making real-time decisions, and handling sensitive data.

From agriculture to surgery and transportation, physical AI and robotics are transforming industries. Robots assist in planting, harvesting, and crop health monitoring, while AI-driven systems revolutionize surgery and Unmanned Aerial Vehicles (UAVs) play a strategic role in logistics, environmental monitoring, public safety and mission-critical operations. As their role expands, so does the urgency to secure them effectively.

The Risks of Unsecured Physical AI and Robotics

AI and robotics are not immune to security risks. As these systems move from digital environments into the physical world, the attack surface expands dramatically, turning every component into a potential target. Without robust cryptographic security solutions, physical AI systems become vulnerable to unauthorized access and tampering.

Attacks on physical AI and robotics platforms fall into two categories: physical attacks and digital attacks. Physical attacks involve the act of physically manipulating hardware with the aim of either disrupting function or obtaining unauthorized access. Digital attacks mainly concern software-related attacks that aim to exploit the vulnerabilities within the physical AI system’s software components. Both may lead to serious consequences for data and safety in the physical world.

Xiphera’s hardware-based security protects critical functions at the hardware level, reducing exposure to these threats.

Physical Attacks

Robust cryptographic solutions and hardware-based security are crucial in mitigating physical attacks (Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities, 2023). These include physically damaging sensors, spoofing, jamming, and manipulation.

Spoofing involves manipulating sensor data, communication signals, or environmental inputs to deceive the AI system into perceiving false reality. One example is LiDAR spoofing, which entails injecting fake laser returns to make a robot “see” obstacles or paths that don’t exist. This can disrupt the robot’s navigation system.

Hardware-based cryptography can significantly reduce the risk of spoofing in robotic systems by ensuring the authenticity, integrity, and confidentiality of sensor data, communication, and control signals. In the LiDAR example, hardware-based solutions can prevent attackers from injecting fake sensor data by using cryptographic data verification.

Another physical attack method is jamming, which refers to overwhelming a physical AI system’s sensors or communication channels with noise, false signals, or excessive data. The goal is to deny service, degrade performance, or force the physical AI system into unsafe operating conditions. Examples of jamming attacks include disrupting military drones with RF noise to force them to land or return to base.

While hardware-based cryptography cannot directly affect physical vulnerabilities of physical AI systems, it can mitigate the impact of jamming and improve overall system resilience by verifying the integrity and origin of received data. By implementing hardware-based encryption (e.g. AES-GCM or AES-XTS) for secondary communication channels, the physical AI system can switch to a secure channel if the primary channel is compromised. Cryptographic keys remain secure for establishing trusted connections post-jamming.

Finally, let’s talk manipulation. Some studies have brought to light the vulnerability of Inertial Measurement Unit sensors (IMUs) employed in robotic systems. Targeted attacks aim to disrupt velocity measurement, which can cause physical AI systems to lose control, leading to accidents and malfunctions.

Hardware-based cryptography can detect tampering, ensure data integrity, and mitigate the impact of physical attacks. If an attacker manipulates IMU data (e.g. by injecting false signals or altering readings), the cryptographic signature will fail verification, and the system rejects tampered data. Hardware-based secure boot ensures that only authenticated firmware runs on both the IMU and the physical AI system’s control unit.

Other Attacks

Physical AI and robotics systems can also suffer from other common cybersecurity attacks, such as backdoor attacks, malware and ransomware.

A backdoor attack is a stealthy technique of bypassing normal authentication methods to gain unauthorized access to a system and remotely control it. Malware can target systems such as surgical robots, enabling the attacker to track the movements of the robot’s arm and trigger the attack payload during important tasks. Ransomware attacks in the context of industrial robots attempt to lock them to extort ransom from the manufacturer.

Hardware-based cryptography can mitigate these risks by preventing unauthorized or malicious firmware (containing backdoors, malware or ransomware) from executing and authorizing only authenticated, unaltered code runs.

The consequences of unsecured physical AI and robotics are severe. Compromised systems in autonomous vehicles, surgical robots, or industrial machinery can lead to accidents, injuries, or even fatalities. Sensitive data breaches expose users and organizations to harm, while critical infrastructure disruptions result in downtime, financial losses, or safety hazards.

These examples are just a glimpse of the risks posed by unsecured physical AI and robotics. They highlight the urgent truth: cryptographic security solutions are essential to safeguarding the integrity, reliability, and safety of AI-driven systems in our physical world.

More on Why Hardware-Based Security is a Game Changer

We’ve explored how hardware-based cryptography protects physical AI systems and touched some of its advantages along the way. Let’s bring these benefits together to see why it’s a true game changer.

Hardware-based cryptography addresses the challenge of keeping physical AI and robotics systems secure by embedding security directly into the physical components of a device. Hardware-based security is more resistant to tampering, reverse engineering, and malicious modifications, making it ideal for physical AI applications where unauthorized access could have catastrophic consequences.

Trust in physical AI and robotics systems needs to be founded on consistent reliability, which is something updatable software cannot provide. Security architectures like hardware root of trust and secure boot are not only designed as inherently trusted foundations, but they also make sure that after initiation, the integrity and authenticity of firmware and configuration of a device is verified, which counters logical attacks. Additionally, a secure update mechanism ensures that when logical vulnerabilities are identified, they can be mitigated.

Security isn’t just about protection; it’s also about performance. Physical AI and robotics often demand real-time decision-making, where even milliseconds of delay can make the difference between safety and disaster. Software-based cryptography often introduces latency, creating bottlenecks that compromise real-time responsiveness. Hardware-based cryptography offers optimised latency and ensures consistent, predictable execution of security operations. By offloading these tasks to dedicated hardware, systems can maintain the precision, speed and reliability required for life-critical applications.

Hardware security IP is optimized for specific cryptographic tasks, consuming significantly less power compared to software. This efficiency is critical for battery-powered robots, drones, and edge AI devices, where energy consumption directly affects operational lifespan.

Hardware-based cryptography doesn’t just secure physical AI and robotics. It enables them to operate at their full potential, delivering both trust, energy efficiency, and real-time performance.

Conclusion

In the age of physical AI and robotics, security is everything. Digital attacks and physical attacks like spoofing, jamming, and manipulation threaten not only the functionality of these systems but also the safety and security of environments and people they interact with.

Hardware-based cryptography provides a robust foundation for securing physical AI and robotics. By embedding security directly into hardware, we can authenticate sensor data, protect communication channels, and ensure the integrity of critical systems. Hardware-based solutions offer resilience against tampering, real-time performance for life-critical applications, and energy efficiency for battery powered devices.

Xiphera specialises in hardware-based security, addressing the unique challenges of physical AI and robotics with solutions that are as innovative as they are reliable. As these technologies continue to evolve, so must our commitment to safeguarding them. The future of AI and robotics isn’t just about what they can do; it’s about ensuring they can do it securely, efficiently, and without compromise.

By prioritizing hardware-based security today, we pave the way for a safer, more trustworthy integration of physical AI and robotics into our daily lives. This way we’re protecting not just the systems themselves, but the people and industries that depend on them.

Sources:

Neupane et al. (2023): “Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities”. IEEE Access (Peer-reviewed journal by the Institute of Electrical and Electronics Engineers).