Hybrid Post-quantum Secure Wireless Healthcare Network Using Ml-kem, Ml-dsa, Blockchain Audit Logging and Ai-based Intrusion Detection

Imagine your body is a bustling city, and tiny sensors are the messengers running through the streets, carrying urgent news about your heart rate, temperature, and oxygen levels to a central command center. This is the world of Wireless Body Area Networks (WBANs), a technology that lets doctors watch over patients from miles away. But right now, these messengers are running through an open field. Anyone with a radio can listen in, steal the messages, or even trick the messengers into delivering fake news. Worse, there's a looming threat on the horizon: a super-powerful "quantum computer" that, in the future, could crack the current locks on these messages, revealing secrets we thought were safe forever. It's like writing a diary in a code that looks unbreakable today, but a future super-computer could read it tomorrow.

To stop this, scientists are building a new kind of security fortress. They are swapping out the old locks for "post-quantum" ones—mathematical puzzles so complex that even a quantum super-computer would struggle to solve them. They are also adding a "black box" ledger that records every single message in a chain, so if anyone tries to sneakily change a past entry, the whole chain breaks and screams "tamper!" Finally, they are hiring a digital guard dog, powered by artificial intelligence, to sniff out suspicious behavior that looks normal on paper but feels wrong in the air. This paper is about building that entire fortress, testing it, and seeing if it can actually keep the peace.

The Paper's Big Idea: A Super-Secure Health Network

The authors of this paper, Veera Venkata Ravi Teja Sunnam and D. Latha, decided to build a complete, working prototype of this super-secure health network. They didn't just draw a picture of it; they coded it, ran it, and tested it against eight different types of digital attacks to see if it would hold up.

The New Locks: ML-KEM and ML-DSA
First, they replaced the old, vulnerable locks with two new, super-strong ones based on the latest NIST standards.

• ML-KEM (The Key Exchange): Imagine a sensor and a gateway trying to agree on a secret password without anyone else hearing them. They use ML-KEM to do this in a single, lightning-fast step. It's like two people shaking hands and instantly knowing a secret code, without needing a long conversation that a spy could eavesdrop on.
• ML-DSA (The Digital Signature): This is the ID card. Every single message sent gets a unique digital signature. If a hacker tries to forge a message or change the data, the signature won't match, and the gateway will reject it immediately.

The Unbreakable Chain: Blockchain Audit Logging
Once a message passes the security checks, it gets written into a "blockchain ledger." Think of this as a magical notebook where every new page is glued to the previous one with a special glue that contains a fingerprint of the page before it. If a hacker tries to go back and erase a page or change a number, the glue breaks, and the fingerprint of the next page no longer matches. The whole chain instantly reveals the tampering. The authors verified that this chain remained 100% intact, meaning no one could sneakily edit the history.

The Digital Guard Dog: AI Intrusion Detection
Even with perfect locks, a bad guy might have a valid key (like a stolen sensor) and try to flood the system with garbage messages to crash it. To catch this, the system uses a "Random Forest" AI. This isn't a human reading every message; it's a smart algorithm that looks at the behavior of the traffic. It checks things like: "How fast are these messages arriving?" and "How big are they?" If the pattern looks weird—like a sudden flood of messages—the AI raises an alarm. In their tests, this digital guard dog correctly identified 87% of the different types of attacks, including replay attacks (sending old messages again) and denial-of-service floods.

The Results: How Fast and How Safe?
The team ran their system through a rigorous stress test. Here is what they found:

• Speed: The system was surprisingly fast. It took 147 milliseconds for a message to go from the sensor, get checked, and be confirmed by the gateway. That's faster than a human blink!
• Throughput: It handled 342 packets per second, which is plenty fast for monitoring heart rates and other vital signs.
• Accuracy: The AI correctly classified attacks 87% of the time.
• Integrity: The blockchain audit log was 100% verified as untampered.

They also tested the AI on a different task: figuring out where a sensor was placed on the body (like on the wrist, chest, or arm). Using a dataset called BLEWBAN, the AI guessed the correct position 76.9% of the time. It was best at spotting sensors on the chest and torso but got a bit confused between left and right arms, which makes sense because they look very similar to the system.

What This Paper Does NOT Claim
It is important to know what this paper doesn't say. The authors are very honest about the limits of their work:

• It's a Simulation, Not a Hospital: The tests were done with synthetic (fake) data and simulated attacks, not real patients in a real hospital. The 87% accuracy is based on these simulations, and the authors warn that it needs to be tested on real-world traffic before being trusted in a clinic.
• Hardware Reality Check: The speed measurements were taken on a standard computer. The authors admit they haven't tested it yet on the tiny, low-power chips (like ARM Cortex-M4) that real medical sensors use. The speed might be different on those smaller devices.
• The "Real" Locks: The system is designed to use the new quantum-resistant locks, but in their test environment, they sometimes used a "demonstration" version if the real software libraries weren't available. They emphasize that for the system to be truly quantum-proof, the real, certified libraries must be installed.
• Not a Doctor: The dashboard shows vital signs and AI alerts, but the authors state clearly that this is a security tool, not a medical diagnostic tool. The AI's "biomarker scores" are just experimental visualizations, not validated medical advice.

The Takeaway
This paper proves that it is possible to build a wireless health network that is ready for the quantum future. By combining new math-based locks, an unchangeable audit trail, and a smart AI guard dog, they created a system that successfully blocked tampering, forgery, and flooding in their tests. While it needs more testing on real hardware and real patients, it offers a clear, working blueprint for keeping our health data safe in a world where quantum computers might one day break today's secrets.