Belgacem Bouallegue

Joint Watermarking\Encryption image for safe transmission: Application on medical imaging

This work presents a new approach of a joint Watermarking/ Encryption algorithm applied in medical domain such as telemedicine, hence the need to keep the visual aspect of medical images and other conservation of the various substituted data. For hiding information, the proposed method uses the Discrete Cosine Transform (DCT) space. For more robustness, the Advanced Encryption Standard (AES) encryption algorithm is proposed. To control identification and eventually the correction (if possible) of the data inserted, it should be noted that we used the serial turbocode to recover the data inserted and after application of several attacks. For evaluation, the IRM images are used. Our proposed method is tested against several attacks, such as the compression, noise, filtering and geometric transformations attacks.

A high-speed AES design resistant to fault injection attacks

To secure the Advanced Encryption Standard against physical attacks known as fault injection attacks, different countermeasures have been proposed. The AES is used in many embedded systems to provide security. It has become the default choice for security services in numerous applications. However, the natural and malicious injected faults reduce its robustness and may cause private information leakage. In this paper, we study the concurrent fault detection schemes for achieving a reliable AES implementation. We specifically propose a new fault detection scheme based on modification of the AES architecture. For this purpose, the round AES transformation is broken into two parts and a pipeline stage is inserted in between.The proposed scheme is independent of the way the S-Box and the Inv_S-Box are implemented. Hence, it can be used for both the S-Box and the Inv_S-Box using Look-Up Table and those using logic gates based on Galois Fields. Our simulation results show the fault coverage reaches 98.54% for the proposed scheme. Moreover, the proposed and the previously reported fault detection schemes have been implemented on the most recent Xilinx Virtex FPGAs. Their area overhead, the frequency and throughput have been compared and it is shown that the proposed fault detection scheme outperform the previously reported ones.

Cryptography of medical images based on a combination between chaotic and neural network

This study presents a novel chaotic–neural network of image encryption and decryption image applied to the domain of medical. The main objective behind the proposed technique is to ensure the safety of medical images with a less complex algorithm compared with the existing methods. In order to improve the robustness, the totality of the pixels related to the host image is XORed with a generation key. After that, with a chaotic system (logistic map), the binary sequence is generated in order to set the weights wij and bias bi of neuron network with the goal of encrypting the pixels issued from the previous step. Simulation and experiments were carried out on medical images coded on 8 and 12 bits/pixel. The obtained results confirmed the performance and the efficiency of the proposed method, which is compliant with Digital Imaging and Communications in Medicine standards.

Fuzzy logic-based hardware architecture for event detection in Wireless Sensor Networks

In this paper, we present and evaluate a hardware multi-sensor architecture for objects / events detection, especially designed to enable low power and higher precision in Wireless Sensor Networks. The proposed architecture is based on fuzzy logic approach in order to improve mapping between QoS requirements for a communication processes and available hardware resources in WSN nodes. It improves the accuracy in taking decision about a system that has imprecise information. Each node introduces two types of sensors, scalar and visual. Scalar sensors perform detection and localization of objects, while the other visual is responsible to monitoring objects. A set of fuzzy rules to analyze signals collected by different sensors is used to activate rest of the sensing circuits (i.e., data processing and communication) only when the event of interest in the environment is available. We discuss in depth the internal hardware architecture of the proposed solution which is planned to reach high performance running in FPGAs circuit. Synthesis results and relevant performance comparisons with related works are presented.

Quantitative evaluation of chaotic CBC mode of operation

The cipher block chaining (CBC) block cipher mode of operation presents a very popular way of encrypting which is used in various applications. In our previous research work, we have mathematically proven that, under some conditions, this mode of operation can admit a chaotic behavior according to Devaney. In this paper, we have developed the quantitative study of this chaotic CBC mode of operation by evaluating both its level of sensibility and expansivity.

Crypto-compression of medical image based on DCT and chaotic system

This paper proposes a crypto-compression scheme to protect the distribution and storage of digital medical images. The proposed process uses a chaotic system in order to provide an efficient digital medical images encryption. This enhanced scheme combines between compression based on DCT and encryption. Simulation experiment, sensitivity and statistical analyses have validated the effectiveness of the proposed system.

An efficient fault detection scheme for the secure hash algorithm SHA-512

To protect the implementation of the standard Secure Hash Algorithm (SHA) against attacks. We have proposed a number of countermeasures. This paper present a proposed new fault detection scheme. It is based on the hybrid redundancy. The simulation results prove that the fault coverage achieves 99.999% for our scheme proposed. Also, our proposed detection scheme has been implemented on Xilinx Virtex-II Pro FPGA. It is fault coverage, area degradation, frequency, throughput and efficiency overhead have been compared and it is shown that the proposed scheme allows a trade-off between the security and the implementation cost of the SHA implementation.

Software application for simulation-based AES, RSA and elliptic-curve algorithms

In this paper we represent a developing work in an advanced algorithm for image encryption. First, we have programmed a flexible encrypting algorithms based on AES, RSA and elliptic-curves methods for text encrypting. Second, we have integrated this algorithms to encrypt compressed images. Finally we have provided a fair comparison between the three most famous encryption algorithms: AES, RSA and elliptic curves. Since the objective here is the efficacy of the algorithms under different settings, the behavior and the performance are taken into consideration in this study comparison of the algorithm when different data loads are used. The presented comparison is based on these parameters: key size, block size and speed. The software application is implemented using C programming.

Implementation of the RN Method on FPGA using Xilinx System Generator for Nonlinear System Regression

In this paper, we propose a new approach aiming to ameliorate the performances of the regularization networks (RN) method and speed up its computation time. A considerable rapidity in totaling calculation time and high performance were accomplished through conveying difficult calculation charges to FPGA. Using Xilinx System Generator, a successful HW/SW Co-Design was constructed to accelerate the Gramian matrix computation. Experimental results involving two real data sets of Wiener-Hammerstein benchmark with process noise prove the efficiency of the approach. The implementation results demonstrate the efficiency of the heterogeneous architecture, presenting a speed-up factor of 40-50 orders of time, comparing to the CPU simulation.

An Enhencment Medical Image Compression Algorithm Based on Neural Network

The main objective of medical image compression is to attain the best possible fidelity for an available communication and storage [6], in order to preserve the information contained in the image and does not have an error when they are processing it. In this work, we propose a medical image compression algorithm based on Artificial Neural Network (ANN). It is a simple algorithm which preserves all the image data. Experimental results performed at 8 bits/pixels and 12bits/pixels medical images show the performances and the efficiency of the proposed method. To determine the ‘acceptability’ of image compression we have used different criteria such as maximum absolute error (MAE), universal image quality (UIQ), correlation and peak signal to noise ratio (PSNR).