Chaotic maps have good potential in security applications due to their inherent characteristics relevant to cryptography. This paper introduces a new audio cryptosystem based on chaotic maps, hybrid chaotic shift transform (HCST), and deoxyribonucleic acid (DNA) encoding rules. The scheme uses chaotic maps such as two-dimensional modified Henon map (2D-MHM) and standard map. The 2D-MHM which has sophisticated chaotic behavior for an extensive range of control parameters is used to perform HCST. DNA encoding technology is used as an auxiliary tool which enhances the security of the cryptosystem. The performance of the algorithm is evaluated for various speech signals using different encryption/decryption quality metrics. The simulation and comparison results show that the algorithm can achieve good encryption results and is able to resist several cryptographic attacks. The various types of analysis revealed that the algorithm is suitable for narrow band radio communication and real-time speech encryption applications.
Secured speech communication plays a significant role in military, voice over Internet protocols, confidential voice conferences, and corporate sectors. This necessitates the development of a reliable, fast, and robust security system to provide data confidentiality, integrity, and authentication. In this regard, researchers have developed many cryptographic algorithms to suite the evolvement in wireless communication technologies. The traditional symmetric cryptographic schemes such as advanced encryption standard (AES) and data encryption standard (DES) can attain high level of security. But they have small key space which in turn suffers from brute force attack. These cryptographic algorithms cannot be utilized in real-time speech encryption due to high degree of redundancy among the samples, bandwidth expansion of the encrypted signal, and reduction of signal to noise ratio performance. Because of complex permutation process, these algorithms require more computational time and high computing power. Further, asymmetric encryption algorithms are not suitable for encryption owing to slow speed and complexity [
In this contest, many researchers have identified the possibility of applying dynamic and disordered behavior of chaotic system in cryptography. These chaotic systems have outstanding features such as high sensitivity to initial conditions/system parameters, erratic behavior, high security, and simplicity. These subtle nonlinear properties make them a novel and efficient way of providing secured speech communication with low complexity. However, there are some challenges that need to be faced when using chaos theory in the field of cryptography [
In order to make chaos based cryptosystem more secure, DNA technology has been infiltrated due to its exclusive characteristics such as huge parallelism, enormous information storage, and ultralow power consumption [
The organization of the paper is as follows. Section
This section reviews the chaotic maps used for speech encryption such as MHM and standard map (SM) along with their dynamical behavior. The comparison of dynamical behaviors of MHM and HM through bifurcation diagram is also considered. Further, the basics of DNA encoding along with algebraic operations is presented.
The modified Henon map [
(a) Bifurcation diagram of Henon map for the system parameter
The 2D standard map is the simplest conservative system which originates from the field of particle physics [
A single DNA sequence is composed of four nucleic bases, namely, adenine (A), cytosine (C), guanine (G), and thymine (T). According to DNA rules, A pairs with T and C pairs with G, where A and T are complementary and C and G are complementary [
DNA encoding and decoding rules.
A | T | C | G | |
---|---|---|---|---|
Rule |
00 | 11 | 10 | 01 |
Rule |
00 | 11 | 01 | 10 |
Rule |
11 | 00 | 10 | 01 |
Rule |
11 | 00 | 01 | 10 |
Rule |
10 | 01 | 00 | 11 |
Rule |
01 | 10 | 00 | 11 |
Rule |
10 | 01 | 11 | 00 |
Rule |
01 | 10 | 11 | 00 |
DNA XOR operation.
A | T | C | G | |
---|---|---|---|---|
A | A | T | C | G |
T | T | A | G | C |
C | C | G | A | T |
G | G | C | T | A |
In this section, the detailed architecture HCST and DNA encoding mechanism adopted for speech encryption is presented. The algorithm uses chaotic maps and DNA encoding to perform primitive operations of cryptography such as confusion and diffusion. These two chaotic maps generate the secret key for the proposed algorithm. The secret key contains the information of initial conditions and control parameters of these maps. Hence, the key set used for encryption/decryption is (
Proposed encryption scheme flow diagram.
In this section, hybrid chaotic shift transform [
Firstly, generate
Let
In this section, the dynamic DNA encoding mechanism is presented to change the value of the speech samples thereby spreading the effect of plaintext across the ciphertext. In order to enhance the security, the dynamic DNA coding is used instead of fixed coding. The values in the confused speech block are converted to their equivalent decimal values by using 16-bit quantization. The detailed operation of DNA encoding scheme is described and shown in Algorithm
An example of DNA encoding process.
An efficient encryption algorithm should satisfy mainly two objectives: (
In order to evaluate the encryption capability of the proposed algorithm, different American English speech signals with sampling rate of 8 KHz and 16 KHz are encrypted. The original, encrypted, and decrypted speech signal are shown in Figure
(a) Original speech signal (Julia 8). (b) Original signal for first frame. (c) Corresponding Encrypted speech signal. (d) Decrypted speech signal.
It has been revealed in the literature that statistical analysis effectively evaluates the cryptosystem [
Histogram analysis evaluates the cryptosystem to determine its ability to resist against statistical attacks. Figure
Histogram of (a) clean speech signal (Mel 8) and (b) encrypted speech signal.
Correlation coefficient (CC) is one of the statistical measures which determine the encryption quality of the cryptosystem. This analysis measures the correlation between the two speech samples whose value lies between −1 and +1. The correlation coefficient being near zero indicates the weakest relationship between the two samples and it is not possible to predict the secret key by the attackers [
Encrypted signal quality metrics.
Name | Correlation between original and encrypted signal | Alwahbani and Bashier [ |
Sheela et al. [ |
PRD |
---|---|---|---|---|
Claire 8 | −0.00021724 | −0.0014 | 0.00001855 |
|
Julia 8 | −0.0028 | 0.0017 | −0.0037 |
|
Lauren 8 | 0.0053 | −0.0031 | −0.0018 |
|
Mel 8 | 0.0043 | 0.0019 | −0.0010 |
|
Ray 8 | 0.000038157 | −0.00016 | 0.0001474 |
|
Rich 8 | −0.0016 | −0.0056 | −0.0035 |
|
Claire 16 | −0.00032371 | −0.0044 | 0.0007885 |
|
Julia 16 | −0.00086778 | 0.0014 | −0.0030 |
|
Lauren 16 | −0.0015 | 0.0059 | 0.0031 |
|
Mel 16 | −0.000266126 | 0.0017 | −0.0041 |
|
Ray 16 | 0.00074651 | −0.0047 | −0.0029 |
|
Rich 16 | −0.00016772 | −0.0017 | −0.0013 |
|
Correlation between the samples in (a) original speech signal (Rich 8), (b) encrypted speech signal, and (c) decrypted speech signal.
Comparison of proposed method with existing method with respect to correlation coefficient between samples of original speech signal and encrypted speech signal.
This parameter measures the deviation of the encrypted speech signal from original signal [
It is necessary to measure and compare the quality of the decrypted signal with that of the original signal in order to prove the efficiency of the cryptosystem. The two approaches, namely, objective and subjective metrics, have been adopted in the literature to verify the quality of the decrypted signal. In objective metrics, the quality is measured using physical parameters and computational models. The subjective speech quality metrics require a panel of trained listeners which itself is a very tedious process. In real-time applications, the objective metrics are desirable because they give more consistent results in a shorter period [
SNR is used to measure residual intelligibility of the encrypted signal and quality of the decrypted signal. Generally, the encrypted signal is characterized by low SNR value indicating the higher noise level than the original speech signal whereas the good quality decrypted signal is characterized by high SNR value. The SNR [
Decrypted signal quality metrics.
Name | SNR in dB | Alwahbani and Bashier [ |
Sheela et al. [ |
PESQ |
---|---|---|---|---|
Claire 8 | 193.6586 | 30.2338 | 31.7008 | 3.34962 |
Julia 8 | 192.7466 | 29.5594 | 24.9047 | 3.28308 |
Lauren 8 | 194.1332 | 30.6980 | 19.1031 | 3.43439 |
Mel 8 | 193.9288 | 30.9975 | 22.4523 | 4.50000 |
Ray 8 | 194.6899 | 30.8710 | 25.2435 | 4.50000 |
Rich 8 | 194.9421 | 31.6812 | 21.7338 | 3.67965 |
Claire 16 | 190.6556 | 32.2487 | 25.0827 | 3.29362 |
Julia 16 | 189.6684 | 32.5668 | 17.3681 | 3.23237 |
Lauren 16 | 191.1387 | 33.7090 | 28.6808 | 3.37061 |
Mel 16 | 190.9293 | 33.8067 | 10.7542 | 4.50000 |
Ray 16 | 191.6308 | 32.8276 | 31.3426 | 4.50000 |
Rich 16 | 191.8984 | 34.6931 | 19.6978 | 3.64210 |
Key sensitivity test on encryption process: (a) original speech signal for first frame (Lauren 8); (b) encrypted speech signal for original key; (c) encrypted signal for Key A.
PESQ is one of the widely used and reliable methods used to measure the quality of the decrypted signal. Higher value of the PESQ indicates the better quality of the recovered speech signal. The PESQ score ranges from 1.0 to 4.5 [
The key space of the encryption algorithm should be larger than
A secure cryptosystem should be extremely sensitive to its secret key in order to resist exhaustive attack. The effect of key sensitivity on encryption process is verified by using slightly different keys to encrypt the same plaintext. A test speech signal “Lauren 8” is encrypted using the secret key
Key sensitivity results for encryption process test signal as “Lauren 8.”
Parameter changed with variation of |
Key obtained | CC between two encrypted signals |
---|---|---|
|
Key A | 0.0025 |
|
Key B | 0.0050 |
|
Key C | −0.0056 |
|
Key D | −0.0035 |
Key sensitivity results for decryption process test signal as “Claire 8.”
Key used | CC between original and decrypted signal | PESQ |
---|---|---|
Key A | −0.0099 | 1.3352 |
Key B | −0.0030 | 0.6341 |
Key C | 0.0021 | 1.0854 |
Key D | 0.0075 | 1.7541 |
The decryption process is analyzed through key sensitivity test by decrypting the encrypted signal with slightly modified key. Figure
Key sensitivity test on decryption process: (a) original speech signal for the first frame (Claire 8); (b) decrypted speech signal for Key B.
The effect of noise needs to be considered in order to evaluate the efficiency of the cryptosystem. Hence, the performance of the cryptosystem is evaluated in the presence of noise for the test speech signal “Ray 8.” In order to evaluate the performance of the cryptosystem, the white Gaussian noise varying from 0 to 45 dB is added to the original signal. The effects of noise on objective metrics such as PESQ and log likelihood ratio (LLR) [
Speech quality metrics for the decrypted signal in the presence of AWGN noise: (a) PESQ; (b) LLR.
Further, in order to evaluate the algorithm the clean speech sentences which are corrupted by babble noise varying from 0 to 10 dB are considered. These signals are taken from NOIZEUS database for experimentation [
Speech quality metrics for the decrypted signal in the presence of babble noise: (a) SNR; (b) PESQ.
The time required to encrypt/decrypt the plaintext depends on various factors such as configuration of the system, programming language, and operating system. The environment used for experimental findings is MATLAB 2009 on 1.88 GHz Intel CPU with 2.99 GB RAM in Windows XP Professional operating system. The average encryption and decryption time taken by the cryptosystem for a speech signal with sampling rate of 8 KHz are 59.65358 s and 27.19384 s, respectively. The cryptosystem uses dynamic DNA coding mechanism in order to increase the security which in turn impacts the speed to some extent. The existing algorithm in [
In this paper, a new speech encryption scheme based on chaotic maps and DNA encoding is proposed. The algorithm uses chaotic maps such as 2D-MHM and SM along with HCST. The modified Henon map has broad chaotic range over an extensive range of system parameters when compared to seed map. Further, in order to increase the security of the cryptosystem DNA encoding technology is integrated. The performance of the cryptosystem is evaluated and compared with existing algorithms. Extensive simulation results show that the proposed algorithm can encrypt different types of speech signals with a high security level and resist several attacks. The algorithm offers more security when compared with the existing algorithm. Further, the algorithm can tolerate different types of noise with high SNR. Therefore, the proposed algorithm can be used in real-time speech encryption applications, secured telephone, and narrow band radio communication.
The authors declare that there are no conflicts of interest regarding the publication of this paper.