SRAM-Based PUF Readouts.

Large-scale parameter characterization of Physical Unclonable Functions (PUFs) is of paramount importance in order to assess the quality and thus the suitability of such PUFs which would then be developed as an industrial-grade solution for hardware root of trust. Carrying out a proper characterization requires a large number of devices that need to be repeatedly sampled at various conditions. These prerequisites make PUF characterization process a very time-consuming and expensive task. Our work presents a dataset for the study of SRAM-based PUFs on microcontrollers; it includes full SRAM readouts along with internal voltage and temperature sensors of 84 microcontrollers of STM32 type. Data has been gathered with a custom-made and open platform designed for the automatic acquisition of SRAM readouts of such devices. This platform also provides possibilities of experimenting aging and reliability properties.

Design and Analysis of a True Random Number Generator Based on GSR Signals for Body Sensor Networks.

Today, medical equipment or general-purpose devices such as smart-watches or smart-textiles can acquire a person's vital signs. Regardless of the type of device and its purpose, they are all equipped with one or more sensors and often have wireless connectivity. Due to the transmission of sensitive data through the insecure radio channel and the need to ensure exclusive access to authorised entities, security mechanisms and cryptographic primitives must be incorporated onboard these devices. Random number generators are one such necessary cryptographic primitive. Motivated by this, we propose a True Random Number Generator (TRNG) that makes use of the GSR signal measured by a sensor on the body. After an exhaustive analysis of both the entropy source and the randomness of the output, we can conclude that the output generated by the proposed TRNG behaves as that produced by a random variable. Besides, and in comparison with the previous proposals, the performance offered is much higher than that of the earlier works.

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

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.

On the Entropy of Oscillator-Based True Random Number Generators under Ionizing Radiation.

The effects of ionizing radiation on field-programmable gate arrays (FPGAs) have been investigated in depth during the last decades. The impact of these effects is typically evaluated on implementations which have a deterministic behavior. In this article, two well-known true-random number generators (TRNGs) based on sampling jittery signals have been exposed to a Co-60 radiation source as in the standard tests for space conditions. The effects of the accumulated dose on these TRNGs, an in particular, its repercussion over their randomness quality (e.g., entropy or linear complexity), have been evaluated by using two National Institute of Standards and Technology (NIST) statistical test suites. The obtained results clearly show how the degradation of the statistical properties of these TRNGs increases with the accumulated dose. It is also notable that the deterioration of the TRNG (non-deterministic component) appears before that the degradation of the deterministic elements in the FPGA, which compromises the integrated circuit lifetime.

Clasificación de las fracturas toracolumbares: comparación entre las clasificaciones de AO y Vaccaro / Classification of thoracolumbar fractures: a comparison between the classifications of AO versus Vaccaro / Classificação das fraturas toracolombares: comparação entre as classificações de AO e Vaccaro

Las clasificaciones han cambiado en el último medio siglo, la más usada desde la pasada década es la Clasificación AO. En 2004, Vaccaro et al. propusieron el Thoraco-Lumbar Injury Classification and Severity Score (TLICS). MÉTODOS: análisis de la reproductividad inter y intra observador, utilizando el test Kappa, de las dos clasificaciones entre tres niveles distintos de traumatólogos en formación, en 30 casos. RESULTADOS: la reproductividad intraobservador en la clasificación de Vaccaro fue: OI: 0,73; OII: 0,6 y OIII: 0,63. Para la clasificación AO: 0,7; 0,7 y 0,6, respectivamente. Entre las dos clasificaciones: OI: 0,59; OII: 0,7 y OIII: 0,62. La evaluación interobservador para la clasificación de Vaccaro es 0,66 y para la clasificación AO de 0,67. Los puntos críticos: rotación y lesiones del complejo ligamentario posterior. CONCLUSIONES: las dos clasificaciones muestran un buen grado de acuerdo (índice de Kappa). Con la de Vaccaro, se observó un acuerdo global del 69 por cento. Con respecto a la indicación de tratamiento ortopédico, el acuerdo fue el 37 por cento. En la indicación de tratamiento quirúrgico, fue del 29 por cento. Cabe remarcar que dicha clasificación dispone de un nivel impreciso donde se puede optar por cualquiera de los dos tratamientos (TLICS 4), esto se observó en el 3 por cento. No hubo concordancia en el 31 por cento. Las mismas indicaciones para la clasificación AO presentaron un acuerdo global del 67 por cento. Para la indicación ortopédica fue del 32 por cento. Se realizó una indicación quirúrgica en el 21 por cento. En las lesiones clasificadas como A3 (14 por cento), su indicación de tratamiento no es definida con unanimidad entre los observadores.

The classifications have changed in the last half century; the most used from the last decade is Classification AO. In 2004, Vaccaro et al. proposed the Thoraco-Lumbar Injury Classification and Severity Score (TLICS). METHODS: one analysis of the inter and intra observant reproduction by using the Kappa test, of the two classifications between three different levels from orthopedic surgeons in formation in 30 cases. RESULTS: the intraobservant reproduction in the classification of Vaccaro was: OI: 0.73; OII: 0.6, and OIII: 0.63. For the AO classification: 0.7; 0.7 and 0.6, respectively. Between the two classifications: OI: 0.59; OII: 0.7, and OIII: 0.62. The interobservant evaluation for the classification of Vaccaro is 0.66 and for AO classification was 0.67. The tactically important points were rotation and injuries of the later ligamentary complex. CONCLUSIONS: the two classifications show a good degree in agreement (Kappa index). With the Vaccaro, it has been observed a global agreement of 69 percent. Regarding the indication of orthopedic treatment, the agreement was 37 percent. In the surgical treatment indication, it was 29 percent. It is possible to remark that this classification has a vague level where it can be decided on any of the two treatments (TLICS 4). This was observed in 3 percent. There was no agreement in 31 percent. The same indications for classification AO presented a global agreement of 67 percent. For the orthopedic indication, it was 32 percent. A surgical indication was made in 21 percent. In the injuries classified as A3 (14 percent) about the treatment is not defined with unanimity between the observers.

As classificações têm mudado na último metade do século, sendo a mais usada desde a última década, a classificação AO. Em 2004, Vaccaro et al. propuseram a Thoraco-Lumbar Injury Classification (TLICS). MÉTODOS: análise da reprodução inter e intraobservador, utilizando o teste Kappa das classificações entre três níveis distintos de traumatólogos em formação, em 30 casos. RESULTADOS: a reprodução intraobservador na classificação de Vaccaro foi: OI: 0,73; OII: 0,6 e OIII: 0,63. Para a classificação AO, 0,77; 0,7 e 0,6, respectivamente. Entre as duas classificações: OI: 0,59; OII: 0,7 e OIII: 0,62. A avaliação interobservador para a classificação de Vaccaro foi de 0,66 e para a classificação AO de 0,67. Os pontos críticos foram rotação e lesões do complexo ligamentar posterior. CONCLUSÕES: as duas classificações mostram um bom grau de concordância (índice Kappa). Com a de Vaccaro, observou-se concordância global de 69 por ciento. Com respeito à indicação do tratamento ortopédico, a concordância foi de 37 por ciento. A indicação de tratamento cirúrgico foi de 29 por ciento. Cabe salientar que essa classificação dispõe de um nível impreciso em que pode-se optar por qualquer dos dois tratamentos (TLICS 4), o qual foi observado em 3 por ciento. Não houve concordância em 31 por ciento. As mesmas indicações para a classificação AO apresentaram concordância global de 67 por ciento. Indicação ortopédica foi de 32 por ciento. Foi realizada uma cirurgia em 21 por ciento. Nas lesões classificadas como A3 (14 por ciento), a sua indicação de tratamento não foi definida com unanimidade entre os observadores.