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Medical Cybersecurity Platform

The growing needs of scalable healthcare platforms can be effectively addressed with heterogenous multi-processing, I/O flexibility, hardware-based deterministic controls and comprehensive solutions in cybersecurity, safety and machine learning.

Medical Cybersecurity Demonstration Platform

The Ultra96 is a development board built around the Xilinx Zynq UltraScale+ MPSoC. The Ultra96-based medical cyber-demonstrator system was put together to demonstrate how the security building blocks of the Zynq Ultrascale+ MPSoC along with partner IP from MicroArx could come together to protect a medical equipment, as an example a medical patient monitor. This demonstration system developed by Xilinx along with its partners uses the Ultra96 board to compare an unsecured system to a secured and protected platform. The demo is presented using a Jupyter Notebook user interface. The UI helps create attacks on various parts of the system and depending on where the attack originated from, it will protect or attest or if required restore a stored golden copy. It shows how an unprotected “air-gapped” system can be attacked without the end-user realizing the system has been compromised.

White Paper - Risk Management for Medical Device Embedded Systems:
 
Xilinx Medical Webpage:
 
Xilinx Security Webpage:
 
YouTube - An effective Cyber-Attack defense solution for your Healthcare or Industrial ‘Neighborhood’:
 
To purchase the hardware needed for this demonstration platform, please visit the following component pages:
 

 • Avnet Ultra96-V2 SBC w/ UltraScale+ FPGA
   (AES-ULTRA96-V2-G)
   http://avnet.me/ultra96v2

 • Pmod Adapter
   (TEP0006-01)
   http://avnet.me/buy-pmod-adapter

 • Avnet Infineon TPM v2.0 Peripheral Module
   (AES-PMOD-TPM20-SLB9670-G)
   
http://avnet.me/buy-tpm2.0

 • Heart Rate Sensor
   (101010082)
   http://avnet.me/buy-grove-heart-rate-sensor

 

Once you have obtained the necessary hardware, download the Ultra96-V2 SD card image archive, extract the image from the archive, and write the image to the SD card using Balena Etcher or Win32 Disk Imager:

ultra96v2_medical_cyber_security_2018_3_200423.zip
http://avnet.me/ultra96v2-medical-cybersecurity-2018.3
MD5:  EC467FDA8F8C3415E9E238D9FA9A16DF

Detailed instructions and Getting Started Guide COMING SOON!

Security Feature Comparison
Jupyter Notebook Containing Example Code