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Achieving secure communication between an Implantable Medical Device (IMD)inside the body and a gateway outside the body has showed its criticality withrecent reports of hackings. The use of asymmetric cryptography is not apractical solution for IMDs due to the scarce computational and powerresources, symmetric key cryptography is preferred. One of the factors insecurity of a symmetric cryptographic system is to use a strong key forencryption. A solution without using extensive resources in an IMD, is toextract it from the body physiological signals. To have a strong enough key,the physiological signal must be a strong source of randomness and InterPulseInterval (IPI) has been advised to be such that. A strong randomness sourceshould have five conditions: Universality, Liveness, Robustness Permanence andUniqueness. Nevertheless, for current proposed random extraction methods fromIPI these conditions (mainly last three conditions) were not examined. In thisstudy, firstly, we proposed a methodology to measure the last three conditions.Then, using a huge dataset of IPI values, we showed that IPI does not haveconditions of Robustness and Permanence. Thus, extraction of a strong uniformrandom number from IPI value, mathematically, is impossible. Thirdly, ratherthan using the value of IPI, we proposed the trend of IPI as a source for a newrandomness extraction method named as Martingale Randomness Extraction from IPI(MRE-IPI). MRE-IPI satisfies the Robustness condition completely and Permanenceto some level. We, also, used randomness test suites and showed that MRE-IPI isable to outperform all recent randomness extraction methods from IPIs and itsquality is half of the AES random number. To the best of our knowledge, this isthe first work in this area which uses such a comprehensive method and largedataset to examine the randomness of a physiological signal.

Extracting Randomness From The Trend of IPI for Cryptographic Operators in Implantable Medical Devices