Bruno B. Albert

Complete software defined RFID system using GNU radio

In this paper we describe a complete Radio Frequency Identification (RFID) system, reader and tag, using the approach of software defined radio (SDR). We use the open source GNU Radio development toolkit to implement this SDR. The advantage of this approach is the possibility of to implement and test RFID applications using a flexible software platform. RFID readers in SDR have already been developed by others researchers, and our main contribution is the implementation of an RFID tag in accordance with EPC Gen2 RFID standard. The system is evaluated and it shown that it works with good performance, and as an example of application we implemented a cryptography protocol proposed to RFID.

An efficient simulation method of communications systems with turbo codes

The authors present an efficient method to estimate the performance of turbo codes with soft output Viterbi algorithm (SOVA) iterative decoding via importance sampling (IS). The method is based on computing a specific decoding error probability of all relevant error centers. The accuracy and viability of the proposed method are demonstrated by two examples. The method is particularly effective at high signal to noise ratio (SNR), where Monte Carlo (MC) simulation takes too much time to obtain an estimative that is statistically sound.

Statistical classification of contamination in glass insulators by reading its spectrum

This paper proposes to use a statistical approach for classifying the contamination level of insulators used in high voltage transmission lines. This studied case considers the voltage applied on glass insulators used in a chain of six elements of a 69 kV power line. When submitted to high voltage, the insulators radiate radio frequency signals up to frequencies of some GHz. In this frequency range the signal can be detected using portable antennas, and then be applied to post processing. These received spectra are analyzed by statistical methods, mean and standard deviation, and the cross relation between them is used to classify the pollution level in insulators. To reduce complexity and cost a simple data processing using the mean and the standard deviation are used. Two types of glass insulators are considered: clean or polluted, and to cover the entire frequency range from 30 MHz to 1 GHz two types of antennas were needed. The results obtained with the mean and the standard deviation show that the first 100 MHz bandwidth can be used for statistical of the insulator pollution level.

Truncated importance sampling simulation applied to a turbo coded communication system

The authors present and demonstrate an efficient method to estimate the bit error rate (BER) of turbo codes via a truncated importance sampling (TIS). The TIS method is based on the relevant code words that effectively contribute to the total BER. In order to find out these code words, a fast algorithm is proposed. Two examples are presented to describe the TIS method. The method is particularly effective at high signal to noise ratio (SNR), where Monte Carlo (MC) simulation takes too much time to obtain an estimative that is statistically sound.

Biometrics-Based Secret Key Agreement by Public Discussion with RFID System

Cryptographic keys based on biometrics, besides offering information security and privacy, have the advantage of being strongly linked to the user. Three main techniques use biometric data to obtain cryptographic keys: cryptographic key release, cryptographic key generation and cryptographic key regeneration. The main objectives of these schemes are to ensure revocability and produce keys with high entropy. In this work, we propose a new technique for secret key agreement based on biometrics. Three security factors are used, represented by an iris code, an RFID tag and a password. The use of the protocol for reconciliation between the RFID reader and tag enables the agreement of a symmetric key with high entropy by discarding all the mismatching bits present in genuine samples, while it fails to do so for impostors that are therefore rejected. A new secret key is agreed after every positive authentication, increasing the security of the system. The system was evaluated on the public database ICE2005 and obtained a 270 binary digit cryptographic key with estimated entropy of about 156 bits at 0% False Acceptance Rate (FAR) and 3.68% False Rejection Rate (FRR).

Transformadas Quânticas de Fourier e de Hartley

Resumo— Uma descoberta notável ocorrida na área da teoria da informação e computação quântica foi a prova de existência de um algoritmo quântico para fatoração de inteiros de n− bits com complexidade O(n log n log log n) operações. Este algoritmo é exponencialmente mais eficiente que o melhor algoritmo clássico correspondente que exige O(exp(n log)) operações. A razão para a eficiência do algoritmo quântico mencionado é a existência de um algoritmo para o cálculo da transformada de Fourier quântica (QFT) de complexidade O((log N)) enquanto o melhor algoritmo clássico (FFT) tem complexidade O(N log N) para uma instância de tamanho N (em geral N = 2). Este artigo focaliza de modo tutorial a QFT e introduz as transformadas de Hartley quânticas definindo-as e verificando algumas de suas propriedades mais importantes.

Parameter optimization for importance sampling in encoded systems

In this paper we present a new methodology based on the stochastic gradient descent to optimizing parameters of the biased distribution along importance sampling simulations. A particular aspect of the new technique is that of use of multiple parameters for the simulation of each codeword. An example of application estimating the performance of a encoded system is given.

Analysis of the truncation biasing for importance sampling simulation of encoded systems

Importance sampling (IS) simulation of convolutionally encoded communication systems requires choosing code-words distinct of the transmitted one, called error-centers, in order to bent the simulation distribution along the direction of such that centers and so speed up simulation [1], [2]. As in practice it is mandatory to limit the number of error-centers the estimative turns up to be biased. We call truncation bias (DeltaT) the difference between the IS estimative using all error-centers and the IS estimative using a limited number of error-centers. In this paper we employ the results given by Urbanke et alli [3] on the asymptotic input-output weight distribution to analyze the asymptotic behaviour of E* [DeltaT] the expected value of the truncation bias.