Information Security System Based on Chaotic Signals Volodymyr Rusyna, Aceng Sambasb and Mujiartob a Yuriy Fedkovych Chernivtsi National University, Kotsybynsky str. 2, Chernivtsi, 58012, Ukraine b Universitas Muhammadiyah Tasikmalaya, Jl. Tamansari No. KM 2,5, Mulyasari, Kec. Tamansari, Tasikmalaya, Jawa Barat, 46196, Indonesia Abstract In this paper, we present computer modelling and analysis of the chaotic Arneodo system. For demonstrate of these results was used modern software environment LabView. Created programming interface allows to generating, analysis and research of the main information properties of chaotic Arneodo system, focusing on time series of the three chaotic coordinates, phase portraits and Lyapunov exponents. Another programming interface demonstrates the algorithm of masking and decrypt of the information. Keywords 1 Nonlinear, Arneodo, LabView, FPGA, security system 1. Introduction Chaotic signals are used in different technical scientific areas such as engineering, optics, radio electronics, telecommunications, robotics, cybersecurity [1-19]. Chaos theory is a branch of mathematics and physics that studies systems whose dynamics, under certain conditions, largely depend on the initial conditions, making long-term prediction impossible [20, 21]. Because, on the one hand, the dynamics of behavior of such systems corresponds to the laws of physics, and, on the other hand, looks irregular, it is called deterministic chaos. Chaotic systems are nonlinear dynamical systems. Chaotic signals have the following characteristics: sensitive dependence on the initial conditions, unpredictability, similarity to the noise, and difficulty to be deciphered. Therefore, it is especially suitable to be applied to the secure communication field. In many physical systems and their deterministic models, it has been confirmed that in addition to typical behaviors such as reduction to constant, periodic or quasiperiodic behaviors, in some cases trajectories become aperiodic (chaotic) if their parameters, internal variables, or external signals are selected. A great interest is the simulation of the main information properties of chaotic systems. For modelling of these properties and demonstrate results was selected software LabView (LabView-2020 (64-bit version for Windows). 2. Modeling of a chaotic Arneodo system Chaotic Arneodo system is described by equations 𝑥 𝑦; 𝑦 𝑧; (1) 𝑧 𝑎𝑥 𝑏𝑦 𝑐𝑧 𝑑𝑥 where a,b,c,d – system parameters, x,y,z – initial conditions [22]. Figure 1 shows the block diagram that implements of chaotic Arneodo system. The main functional part is a formula node, in which would include the equation (1). In the input formula node fed values ITTAP’2021: 1st International Workshop on Information Technologies: Theoretical and Applied Problems, November 16–18, 2021, Ternopil, Ukraine EMAIL: rusyn_v@ukr.net (A. 1); acenx.bts@gmail.com (A. 2); mujiarto@umtas.ac.id (A. 3) ORCID: 0000-0001-6219-1031 (A. 1); 0000-0002-1623-0770 (A. 2); 0000-0002-4825-8436 (A. 3) © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org) of system parameters (a,b,c,d) and the value of the initial conditions (x,y,z). At the output assigned equations (1). Also, the output is an opportunity to demonstrate the solution of equations in three dimensions. Figure 1: Block diagram of chaotic Arneodo system Figure 2 and Figure 3 shown chaotic attractor in XY, XZ and YZ projection and time series for X, Y and Z coordinates for the following set of parameters: a = -5.5, b = 3.5, c = 1, d = -1; x = 0.5, y = -1, z = 0.5, dt = 0.01, number of iterations N = 10000. Figure 2: Chaotic attractor in XY, XZ and YZ projection Figure 3: Time series for X, Y and Z coordinates To demonstrate of chaotic behavior of the different nonlinear systems can be used Field- Programable Gate Array (FPGA) [23-25]. Figures 4-6 shows chaotic attractor in XY, XZ and YZ projection using FPGA. Figure 4: Chaotic attractor in XY projection Figure 5: Chaotic attractor in XZ projection Figure 6: Chaotic attractor in YZ projection The Lyapunov exponents of the Arneodo attractor are 0.232, 0, and -1.232. 3. Chaotic masking and decryption of the information carrier The coherent receivers usually are dynamical systems that resemble the chaos producing transmitters. They achieve synchronization with the transmitter, enabling the synchronization to extract the information signal from the received chaotic signal. In order to achieve synchronization, the parameters of the transmitter have to be known. They can be considered as the encryption key of the message; thus, coherent receptions allows for some privacy of the information transmission. Figure 7 demonstrates the presence of the chaotic signal between the transmitter and receiver. In this case, the use of chaos in secure communication systems has been proposed. The design of these systems depends on the self-synchronization property of the chaotic attractor. As shown in Figure 7, the transmitter and the receiver systems are identical. Figure 7: Transmitter and receiver systems Figure 8 presents the program interface, which demonstrates the masking of the information carrier based on a chaotic Arneodo system (1). Figure 8: Software interface show’s masking and decryption of the information carrier The masking of the information carrier based on chaos is provided by blending information with the chaotic signal. A sinusoidal signal (useful signal) was used as information (input) with amplitude of 3 V and system parameters a = -5.5, b = 3.5, c = 1, d = -1, dynamic variables x = 0.5, y = -1, z = 0.5. System parameters and dynamic variables are the keys for the masking information. Algorithm for the decryption has opposite effect. 4. Conclusions For modelling of information properties of the chaotic Arneodo system and demonstrate computer modelling results was selected software LabView (LabView-2020 (64-bit version for Windows). The main information properties of chaotic Arneodo system such as a time series of the three chaotic coordinates, phase portraits and Lyapunov exponents are presented. The programming interface demonstrates the algorithm of masking and decrypt of the information carrier. 5. 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