In this study, with an FPGA-board using VHDL, we designed a secure chaos-based stream cipher (SCbSC), and we evaluated its hardware implementation performance in terms of computational complexity and its security. The fundamental element of the system is the proposed secure pseudo-chaotic number generator (SPCNG). The architecture of the proposed SPCNG includes three first-order recursive filters, each containing a discrete chaotic map and a mixing technique using an internal pseudo-random number (PRN). The three discrete chaotic maps, namely, the 3D Chebyshev map (3D Ch), the 1D logistic map (L), and the 1D skew-tent map (S), are weakly coupled by a predefined coupling matrix M. The mixing technique combined with the weak coupling technique of the three chaotic maps allows preserving the system against side-channel attacks (SCAs). The proposed system was implemented on a Xilinx XC7Z020 PYNQ-Z2 FPGA platform. Logic resources, throughput, and cryptanalytic and statistical tests showed a good tradeoff between efficiency and security. Thus, the proposed SCbSC can be used as a secure stream cipher.

This work proposes a new secure chaos-based encryption/decryption system, operating in cipher block chaining (CBC) mode, and analyze its performance. The cryptosystem includes a robust pseudorandom number generator of chaotic sequences (PRNG-CS). A strong chaos-based S-box is proposed to perform a circular substitution operation (confusion process). This PRNG-CS consists of four discrete 1-D chaotic maps, weakly coupled by a predefined coupling matrix M, to avoid, on the one hand, the divide-and-conquer attack and, on the other hand, to improve the generated sequence’s randomness and lengths. The noun is also used in the construction of the S-box. Moreover, a 2-D modified cat map and a horizontal addition diffusion (HAD) preceded by a vertical addition diffusion (VAD) are introduced to perform the diffusion process. The security analysis and numerous simulation results of the main components (PRNG-CS and S-box) as well as the whole cryptosystem reveal that the proposed chaos-based cryptosystem holds up against various types of statistical and cryptographic attacks.

In this paper, we propose, implement, and analyze the structures of two keyed hash functions using the Chaotic Neural Network (CNN). These structures are based on Sponge construction, and they produce two variants of hash value lengths, i.e., 256 and 512 bits. The first structure is composed of two-layered CNN, while the second one is formed by one-layered CNN and a combination of nonlinear functions. Indeed, the proposed structures employ two strong nonlinear systems, precisely a chaotic system and a neural network system. In addition, the proposed study is a new methodology of combining chaotic neural networks and Sponge construction that is proved secure against known attacks. The performance of the two proposed structures is analyzed in terms of security and speed. For the security measures, the number of hits of the two proposed structures doesn’t exceed 2 for 256-bit hash values and does not exceed 3 for 512-bit hash values. In terms of speed, the average number of cycles to hash one data byte (NCpB) is equal to 50.30 for Structure 1, and 21.21 and 24.56 for Structure 2 with 8 and 24 rounds, respectively. In addition, the performance of the two proposed structures is compared with that of the standard hash functions SHA-3, SHA-2, and with other classical chaos-based hash functions in the literature. The results of cryptanalytic analysis and the statistical tests highlight the robustness of the proposed keyed hash functions. It also shows the suitability of the proposed hash functions for the application such as Message Authentication, Data Integrity, Digital Signature, and Authenticated Encryption with Associated Data.

In this paper, we come up with three secure chaos-based stream ciphers, implemented on an FPGA board, for data confidentiality and integrity. To do so, first, we performed the statistical security and hardware metrics of certain discrete chaotic map models, such as the Logistic, Skew-Tent, PWLCM, 3D-Chebyshev map, and 32-bit LFSR, which are the main components of the proposed chaotic generators. Based on the performance analysis collected from the discrete chaotic maps, we then designed, implemented, and analyzed the performance of three proposed robust pseudo-random number generators of chaotic sequences (PRNGs-CS) and their corresponding stream ciphers. The proposed PRNGs-CS are based on the predefined coupling matrix M. The latter achieves a weak mixing of the chaotic maps and a chaotic multiplexing technique or XOR operator for the output function. Therefore, the randomness of the sequences generated is expanded as well as their lengths, and divide-and-conquer attacks on chaotic systems are avoided. In addition, the proposed PRNGs-CS contain polynomial mappings of at least degree 2 or 3 to make algebraic attacks very difficult. Various experimental results obtained and analysis of performance in opposition to different kinds of numerical and cryptographic attacks determine the high level of security and good hardware metrics achieved by the proposed chaos system. The proposed system outperformed the state-of-the-art works in terms of high-security level and a high throughput which can be considered an alternative to the standard methods.