ECG-RNG: A Random Number Generator Based on ECG Signals and Suitable for Securing Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are a promising technology with applications in many areas such as environment monitoring, agriculture, the military field or health-care, to name but a few. Unfortunately, the wireless connectivity of the sensors opens doors to many security threats, and therefore, cryptographic solutions must be included on-board these devices and preferably in their design phase. In this vein, Random Number Generators (RNGs) play a critical role in security solutions such as authentication protocols or key-generation algorithms. In this article is proposed an avant-garde proposal based on the cardiac signal generator we carry with us (our heart), which can be recorded with medical or even low-cost sensors with wireless connectivity. In particular, for the extraction of random bits, a multi-level decomposition has been performed by wavelet analysis. The proposal has been tested with one of the largest and most publicly available datasets of electrocardiogram signals (202 subjects and 24 h of recording time). Regarding the assessment, the proposed True Random Number Generator (TRNG) has been tested with the most demanding batteries of statistical tests (ENT, DIEHARDERand NIST), and this has been completed with a bias, distinctiveness and performance analysis. From the analysis conducted, it can be concluded that the output stream of our proposed TRNG behaves as a random variable and is suitable for securing WSNs.

Securing Next Generation Multinodal Leadless Cardiac Pacemaker System: A Proof of Concept in a Single Animal

“…The IBI is the time elapsed between contiguous heart cycles and varies with time depending on different physiological factors. Other similar works are also available in the literature utilizing heart rate as a random source to generate the cryptographic keys [28]- [33].…”

Review on Using Biometric Signals in Random Number Generators.

“…The study also suggests the results degrade if more than 16-bits are extracted from each heart-beat. Similar application of ECG in Random Number generation is discussed in the paper, "ECG-RNG: A Random Number Generator based on ECG Signals and Suitable for Securing Wireless Sensor Networks" [6]. In the article, "Heartbeats do not make good pseudo random number generators: An analysis of the randomness of the Inter-Pulse Intervals" [5], the suspicion of using IPI as the source of randomness which is the basis of the method suggested in paper [4] is raised.…”

A True Random Number Generator Based on Gait Data for the Internet of You

“…Among the most used entropy sources for TRNGs stand out the solutions that include different kinds of electrical noise [10], [11], clock jitter and coherent sampling [12], metastability [13], [14] and chaos [15], [16]. A new trend, which exploits biosignals (vital information) as a source of entropy, is emerging in the IoT context [17], [18].…”

“…Using wearable body sensors approaches for key generation helps to overcome the stringent power and area constraints of the IoT environment. Deriving cryptographic keys from Electrocardiogram signals (ECG) is the greatest exponent of this trend [17], [19], [20]. Other alternatives exploit different sensor information such as the Galvanic Skin Response (GSR) [21], [22], the electroencephalogram (EEG) signal [23], the blood volume pulse or respiration [24].…”