Designing ECG-based Physical Unclonable Function

Despite the ubiquitous nature of wearables in today’s society, there are increasing concerns with respect to the security and privacy of personal data stored in these devices. Private data and health information stored in wearables require a device and a third party to transmit user information. An authentication method is then required to verify the transmission. This method can be done in many different ways, but advancements in biometric authentication models have led to the exploration of utilizing Electrocardiogram (ECG) signals as a model for developing encryption and decryption methods for private and sensitive information from wearable devices.  Invention DescriptionResearchers at Arizona State University have developed a system for encrypting and decrypting private data on wearable devices using ECG signals. A user’s ECG signals are used as a unique source for making Physical Unclonable Function (PUF) keys for encryption and decryption engines. A signal processing unit embedded in the system detects and filters ECG signals of interest transmitted by the user. Machine learning algorithms then learn the user’s personal ECG signals to generate a unique 256-bit PUF key for encrypting and decrypting information on wearable devices.  Potential Applications Large Scale Security  Private and Secure Health Monitoring Extra Security Layer for Biometric Authentication Benefits and Advantages Active – Access to information is only allowed when worn by the owner Tough – Keys are extremely difficult to reproduce, even by manufacturersIntelligent – System algorithms learn the user’s unique ECG signals as they change over timeEstablished – Tests on the system pass the National Institute of Standards and Technology (NIST) randomness tests For more information about the inventor(s) and their research, please seeJae-sun Seo's Directory Page

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