AI is becoming a big part of embedded systems, and while this brings many benefits, it also creates new security risks. To keep devices safe, developers need stronger protection against cyberattacks.
AI is changing how everyday technology works. Devices that once did simple tasks can now think, learn, and make decisions. We see this in smart cars, factory machines, medical equipment, and even home appliances.
But as these devices get smarter, hackers also find new ways to attack them. This means security needs to improve at the same pace as technology.
Many tech companies have helped bring AI into a wide range of devices. Their powerful hardware makes these systems faster and smarter but also more attractive targets for cybercriminals. The more advanced the technology becomes, the more hackers try to take advantage of any weakness.
This article explains the new risks that come with AI in embedded systems and what developers can do to keep these devices secure.
Emerging Security Risks in AI-Powered Embedded Systems
Today, AI is built into many of the devices people use every day. But adding AI can also open the door to new problems. Many embedded systems have limited memory, stay in use for years, and are easy to access physically all of this makes them vulnerable to cyberattacks.
The market for embedded security is growing fast and is expected to reach over $12 billion by 2032. This shows that more devices are being used, and therefore more hackers are trying to break into them.
Recently, several vulnerabilities were found in NVIDIA GPUs. These issues could allow attackers to disrupt devices or change important data. This happened because of a small misconfiguration in how software components were handled — a tiny mistake that created a large risk.
Powerful devices offer great benefits, but if they are not properly protected, they can become entry points for attackers and lead to financial loss or damage to a company’s reputation.
Everyday Smart Devices Are Becoming Targets
From voice assistants to AI-powered health monitoring devices, embedded systems are increasingly present in homes, businesses, and government settings. As everyday devices become smarter, the likelihood increases that cybercriminals will attempt to access secure data by any means possible, including through smart devices.
The same AI that allows these devices to function seamlessly can also be a weak link in the security chain. For example, AI-powered security cameras or home automation systems can be hacked, enabling cybercriminals to access private footage or even control home security features.
In one instance, researchers discovered that Gemini AI prompts could be used to create an agent that could control Google Home smart devices. Google announced that it had introduced multiple fixes to prevent these promptware vulnerabilities from being manipulated. However, this reveals how cybercriminals are rapidly developing their strategies to discover new vulnerabilities to target smart devices.
AI-powered infrastructure is also becoming increasingly common with companies revealing that its technologies will be used to increase the capabilities of smart cities. This includes AI-powered traffic-management systems. However, as these systems rely on a series of interconnected devices, cyberattacks could have widespread implications, compromising public safety.
Another sector that’s increasingly investing in AI-enabled devices is the medical industry, with hospitals using smart devices to monitor heart rates, deliver insulin, or perform diagnostics. NVIDIA announced significant investments in the healthcare technology industry, with plans to bring AI into hospitals with physical robots to undertake a range of tasks, from X-ray imaging to linen delivery.
Health-monitoring devices, including oximeters and peak flow meters, have also become incredibly popular, with the market for these devices expected to reach $270 billion by 2029. However, research has shown that they face risks such as spoofing, data injection, and manipulation of settings.
If hackers gain control over these systems, they could change settings or even cause a device to malfunction, endangering patient safety.
How to Keep AI-Enabled Embedded Systems Secure
As AI becomes more common in embedded systems, security measures must also advance. Traditional tools like basic firewalls or antivirus programs are no longer enough. Developers need stronger, smarter protection, including:
1. Secure Boot and Chain of Trust
This makes sure the device only runs trusted software. If any part of the system has been changed by an attacker, the device will refuse to start. This prevents hackers from taking control through hidden malware.
2. Data Encryption
Encrypting data protects it during transfer and while stored on the device. Tools like dm-crypt and fscrypt make it harder for attackers to read or steal sensitive information.
3. Backup and Redundancy
Having backup systems ensures the device can keep running even if part of it fails or gets hacked. This helps avoid downtime or dangerous failures.
4. AI for Security Monitoring
AI can also help defend the system. Machine-learning models can watch for unusual behavior and detect threats early — even threats that humans may not notice. This makes the system more proactive and prepared.
Conclusion
Keeping AI-powered embedded systems safe requires a combination of traditional security and modern, AI-driven protection. With the right strategy, developers can build devices that are smart, reliable, and secure. This not only protects users but also builds trust in the technology.
