Over the past decades, the confidentiality of multimedia communications such as audio, images, and video has become increasingly important since communications of digital products over the network (wired/wireless) occur more frequently [1, 2]. Therefore, the need for secure data and transmission is increasing dramatically and defined by the required levels of security depending on the purpose of communication. To meet these requirements, a wide variety of cryptographic algorithms have been proposed.
In this context, the main challenge of stream cipher cryptography relates to the generation of long unpredictable key sequences. More precisely, the sequence has to be random, its period must be large, and the various patterns of a given length must be uniformly distributed over the sequence.
Traditional ciphers like DES, 3DES, IDEA, RSA, or AES are less efficient for real-time secure multimedia data encryption systems and exhibit some drawbacks and weakness in the high stream data encryption [3, 4]. Indeed, the increase and availability of a high-power computation machine allow a force brute attack against these ciphers. Moreover, for some applications which require a high-level computation and where a large computational time and high computing power are needed (for example, encryption of large digital images), these cryptosystems suffer from low-level efficiency [5]. Consequently, these encryption schemes are not suitable for many high-speed applications due to their slow speed in real-time processing and some other issues such as in the handling of various data formatting.
Over the recent years, considerable researches have been taken to develop new chaotic or hyperchaotic systems and for their promising applications in real-time encryption and communication [6–8]. In fact, it has been shown that chaotic systems are good candidates for designing cryptosystems with desired properties [9]. The most prominent is sensitivity dependence on initial conditions and system parameters, and unpredictable trajectories.
Furthermore, chaos-based and other dynamical system-based algorithms have many important properties such as the pseudorandom properties, ergodicity and non-periodicity. These properties meet some requirements such as sensitivity to keys, diffusion, and mixing in the cryptographic context. Therefore, chaotic dynamics is expected to provide a fast and easy way for building superior performance cryptosystems, and the properties of chaotic maps such as sensitivity to initial conditions and random-like behavior have attracted the attention to develop data encryption algorithms suitable for secure multimedia communications. Until recently, chaotic communication has been a subject of major interest in the field of wireless communications. Many techniques based on chaos have been proposed such as additive chaos masking (ACM) [10], where the analog message signal is added to the output of the chaos generator within the transmitter. In [11], chaos shift keying is used where the binary message signal selects the carrier signal from two or more different chaotic attractors. Authors in [12] use chaotic modulation where the message information modulates a parameter of the chaotic generator. Chaos control methods [13, 14] rely on the fact that small perturbations cause the symbolic dynamics of a chaotic system to track a prescribed symbol sequence. In [15], the receiver system is designed in an inverse manner to ensure the recovery of the encryption signal. An impulsive synchronization scheme [16] is employed to synchronize chaotic transmitters and receivers. However, all of these techniques do not provide a real and practical solution to the challenging issue of chaotic communication which is based on extreme sensitivity of chaotic synchronization to both the additive channel noise and parameter mismatches. Precisely, since chaos is sensitive to small variations of its initial conditions and parameters, it is very difficult to synchronize two chaotic systems in a communication scheme. Some proposed synchronization techniques have improved the robustness to parameter mismatches as reported in [16, 17], where impulsive chaotic synchronization and an open-loop-closed-loop-based coupling scheme are proposed, respectively. Other authors proposed to improve the robustness of chaotic synchronization to channel noise [18], where a coupled lattice instead of coupled single maps is used to decrease the master-slave synchronization error. In [19], symbolic dynamics-based noise reduction and coding are proposed. Some research into equalization algorithms for chaotic communication systems are also proposed [20]. For other related results in the literature, see [21–23]. However, none of them were tested through a real channel under real transmission conditions. Digital synchronization can overcome the failed attempts to realize experimentally a performed chaotic communication system. In particular, when techniques exhibit any difference between the master/transmitter and slave/receiver systems, it is due to additive information or noise channel (disturbed chaotic dynamics) which breaks the symmetry between the two systems, leading to an accurate non-recovery of the transmitted information signal at the receiver. In [24], an original solution to the hard problem of chaotic synchronization high sensibility to channel noise has been proposed. This solution, based on a controlled digital regenerated chaotic signal at the receiver, has been tested and validated experimentally in a real channel noise environment through a realized wireless digital chaotic communication system based on zonal intercommunication global-standard, where battery life was long, which was economical to deploy and which exhibited efficient use of resources, known as the ZigBee protocol. However, this synchronization technique becomes sensible to high channel noise from a higher transmission rate of 115 kbps, limiting the use of the ZigBee and Wireless Fidelity (Wi-Fi) protocols which permit wireless transmissions up to 250 kbps and 65 Mbps [25, 26], respectively. Consequently, no reliable commercial chaos-based communication system is used to date to the best of our knowledge. Therefore, there are still plentiful issues to be resolved before chaos-based systems can be put into practical use. To overcome these drawbacks, we propose in this paper a digital feedback hyperchaotic synchronization and suggest the use of advanced wireless communication technologies, characterized by high noise immunity, to exploit digital hyperchaotic modulation advantages for robust secure data transmissions. In this context, as results of the rapid growth of communication technologies, in terms of reliability and resistance to channel noise, an interesting communication protocol for wireless personal area networks (WPANs, i.e., ZigBee or ZigBee Pro Low-Rate-WPAN protocols) and wireless local area network (WLAN, i.e., Wi-Fi protocol WLAN) is developed. These protocols are identified by the IEEE 802.15.4 and IEEE 802.11 standards and known under the name ZigBee and Wi-Fi communication protocols, respectively [25]. These protocols are designed to communicate data through hostile Radio Frequency (RF) environments and to provide an easy-to-use wireless data solution characterized by secure, low-power, and reliable wireless network architectures. These properties are very attractive for resolving the problems of chaotic communications especially the high noise immunity property. Hence, our idea is to associate chaotic communication with the WLAN or WPAN communication protocols. However, this association needs a numerical generation of the chaotic behavior since the XBee protocol is based on digital communications. In the hardware area, advanced modern digital signal processing devices, such as field programmable gate array (FPGA), have been widely used to generate numerically the chaotic dynamics or the encryption keys [27–31]. The advantage of these techniques is that the parameter mismatch problem does not exist contrary to the analog techniques. In addition, they offer a large possible integration of chaotic systems in the most recent digital communication technologies such as the ZigBee communication protocol. In this paper, a wireless hyperchaotic communication system based on dynamic feedback modulation and RF XBee protocols is investigated and realized experimentally. The transmitter and the receiver are implemented separately on two Xilinx Virtex-II Pro circuits [32] and connected with the XBee RF module based on the Wi-Fi or ZigBee protocols [26, 33]. To ensure and maintain this connection, we have developed a VHSIC (very high speed integrated circuit) hardware description language (VHDL)-based hardware architecture to adapt the implemented hyperchaotic generators, at the transmitter and receiver, to the XBee communication protocol. Note that the XBee modules interface to a host device through a logic-level asynchronous serial port. Through its serial port, the module can communicate with any logic and voltage-compatible Universal Asynchronous Receiver/Transmitter (UART) [33]. The used hyperchaotic generator is the well-known and the most investigated hyperchaotic Lorenz system [34]. This hyperchaotic key generator is implemented on FPGA technology using an extension of the technique developed in [27–29] for three-dimensional (3D) chaotic systems. This technique is optimal since it uses directly VHDL description of a numerical resolution method of continuous chaotic system models. A number of transmission tests are carried out for different distances between the transmitter and receiver. The real-time results obtained validate the proposed hardware architecture. Furthermore, it demonstrates the efficiency of the proposed solution consisting on the association of wireless protocols to hyperchaotic modulation in order to build a reliable digital encrypted data or image hyperchaotic communication system.
The remainder of this paper is organized as follows: the ‘Hyperchaotic synchronization and encryption technique’ section proposes an adapted feedback hyperchaotic synchronization based on a dynamic feedback modulation. This section details the proposed synchronization and data masking principle by considering hyperchaotic systems. The ‘FPGA implementation of hyperchaotic Lorenz generator’ section briefly introduces continuous Lorenz hyperchaotic system, which is used as key stream generators of the proposed digital encryption hyperchaotic modulation. This section then details the hardware architecture used for implementing the Lorenz hyperchaotic generator. A register transfer level (RTL) architecture for embedded hardware implementation of the considered key stream generator is also given in this section. The ‘Experimental framework’ section presents our experimental framework used to realize and validate the wireless hyperchaotic communication scheme. This section gives details of the transmitter and the receiver blocks with a short description of the XBee RF modules. The ‘Wireless real-time data or image transmission tests and results’ section presents different real-time results proving that the proposed system is suitable for efficient secure real-time data or image transmissions of wireless sensor networks. Performance analysis through real wireless data transmission tests is also discussed in this section. The ‘Security analysis’ section gives the statistical analysis of the proposed image encryption scheme, which increases the complexity of the random bit generation and hence making it difficult for an intruder to extract information about the proposed encryption/decryption hyperchaotic modulation. Finally, the ‘Conclusions’ section draws appropriate conclusions.