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The X signal at the receiver uses the following equations to
get the slave system’s synchronization with the two systems
(8) [48] :
Wi + 1 = f (Xi,Yi) (8)
Zi + 1 = g(Wi, Zi)
The total voice encryption block diagram employing (SFPCM-
SC) is shown in Fig. 20. For fixed- point PRBGs, five differ-
ent kinds are created, namely FPQM-PRBG, FPHM-PRBG,
FPDM - PRBG, FPLM-PRBG, and FPLoM-PRBG.Henon,
Duffy, Lozi, quadratic, and logistic mapscorrespondingly. The
spoken signal in analog format is sampled using n = 16 res-
olution bits and a sample frequency of fs = 8 kHz is used.
The pre-processing function is used to extract a fixed- point
sequence with a length of 32 words for each sample from the
sampled speech signal (S). After that, the 32-bit sample was
XORed with the key stream bits (Ki)to produce the encryption
bits (Ci). The original i-th bit(S) is recovered at the receiving namical analysis is carried out using analytical and numerical
end by XORing the encryption bits with the synchronized
key stream bits produced on the deciphering side. In order
to restore the original speech signal at the transmitter end,
the conversion procedure is the inverse function of the pre-
processing function.
In 2019, Abd El-Maksoud, et al [49], presented the FPGA
implementation of the Ozoguz, Yalcin, and Tang chaotic sys-
tems, as well as fractional order multi-scrolls. The chaotic
system equations were generalized into the fractional-order
domain using the Grunwald-Letnikov (GL) definition. Ad-
ditionally, each system’s parameter variation was examined
in relation to the GL definition’s window size. To simulate
the design under investigation, Xilinx ISE 14.5 was utilized,
while Artix-7 XC7A100T FPGA was employed for systems
realization. Every fractional system’s FPGA summary was
presented, and a comparative analysis was conducted. The
respective throughputs of Yalcin, Ozoguz, and Tang were
found to be 3.417GHz,1.513GHz, and 2.425GHz, respec-
tively. Since Yalcin had the highest throughput and Ozoguz
had the lowest, Yalcin was selected to be employed in the
speech encryption system. Additionally, the encryption al-
gorithm for speech encryption used the Yalcin system. One
clock latency was used to implement the entire system on
FPGA.
In 2016, Fadhil S. Hasan [50], The author presents the
Fixed-Point Chaos-based Stream Cipher (FPC-SC), which is
Shumran & Al-Hussein
used to encrypt speech signals. The stream cipher system
uses a fixed-point chaos-based pseudo-random bit generator
(FPC-PRBG) as its key sequence. Gold FPC-PRBG is gen-
erated by combining two chaotic Lorenz and Chen systems.
The outcomes demonstrate that FPC-PRBG can be used to
generate high speech security levels and has good statisti-
cal randomness and encryption performance measures. The
Xilinx System Generator (XSG) with Xilinx Virtex 4 FPGA
device is used to implement FPC-PRBG. The system is ac-
cessed and routed in this device with throughputs of 818.64,
7978.88, and 780.24 Mbits/sec for Lorenz, Chen, and Gold
FPC-PRBG, respectively, where 40 bits fixed-point operation
is used.
In 2023, Girma Adam, et al. [51], a three-dimensional
fractional-order chaotic system (FOCS) is created; the sys-
tem has by adding a nonlinear function and the values of its
parameters, equilibria can take on a variety of forms. A dy-
methods in order to understand the behavior of the system
under various situations and parameter values. Phase portraits,
bifurcation analysis, Lyapunov spectra, and Lyapunov expo-
nents (LEs) are some of the methods used in this investigation.
The system exhibits more complex attractors than a standard
chaotic system with an integer value, in particular when the
fractional order q is set to 0.97. It is very suitable for creating
secure communication networks because of its characteristic.
To further demonstrate the system’s viability, a working imple-
mentation built around an electrical circuit has been created.
Two layers of encryption were used in the construction of a
secure communication system.
F. Chaotic Systems Based Pseudo Random Bit Generator
(PRBG)
The PRBG is widely used in many applications such as com-
puter games, cryptography testing, numerical analysis, and
integrated circuits. When creating pseudo-random numbers
to create a binary key stream for encryption, the chaotic sys-
tem’s orbit’s aperiodic, irregular, unpredictable, and sensitive
dependence on initial conditions are useful properties to have:
In 2016, Farsana F J et al [2], suggested a new method for
speech encryption by using diffusion and confusion processes
of the speech samples using Zaslavsky map and cat transform.
Firstly, the original speech signal is converted to the frequency
domain by using discrete cosine transform (DCT) and its bi-
nary information is confused by XORing with the key stream
generated from the two-dimensional chaotic Zaslavsky map.
The result is confused and rearranged by using the cat trans-
form and finally, the resulted signal is converted to the time