This paper proposes the establishment of a secure encryption system for data transmission that includes three stages: first stage is a scrambling stage that is divided into scrambling of different sizes blocks and scrambling bits, the second stage is the use of DNA code to flip the bits and the third stage is the encryption using the Substitution box by 256 keys. The scheme is analysed using a variety of metrics. The findings demonstrate that the proposed system is significantly more reliable and robust against various forms of attacks than several recent related speech signal encryption systems.

/pdf/speech-encryption-technique-using-s-box-based-on-multi-ikmgwwomuv.pdf

Speech Encryption Technique using S - box based on Multi Chaotic Maps

Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file.  This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.

/pdf/secure-image-hiding-in-speech-signal-by-steganography-mining-4gqkl4ksn6.pdf

Secure image hiding in speech signal by steganography-mining and encryption

Abstract: In this paper, an encryption approach for Speech communication based on direct chaotic modulation (non-autonomous modulation) is presented, in which speech signal is injected into one variable of the master system (using Lorenz system) without changing the value of any control parameter. This approach is based on the change of chaotic signal by injecting Speech samples into one variable in chaotic system and hence generating a new chaotic signal. The Speech signal is then extracted from the chaotic signal on the receiver side. Furthermore, a high dimension chaotic system is used, which increases the security of the encrypted signal. Non-autonomous modulation technique is suitable for securing real-time applications. A comparative study of approach and Speech masking technique is also presented. Experimental results show that non-autonomous methods give better performance than their chaotic masking counterparts when they are analyzed against Signal-to-Noise-Ratio (-38.55 dB vs. -35.51 dB), Segmental signal-to-Noise-Ratio (-38.91 dB vs. -35.84 dB), Log-Likelihood Ratio (0.89 vs. 0.80), and Correlation Coefficient Analysis (0.0345 vs. 0.021). Non-autonomous techniques overcome the chaotic masking break and considered more secure.

https://ejle.journals.ekb.eg/article_59392_987a4d2295b216217a1db66f02e8c484.pdf

A Speech Cryptosystem Based on Chaotic Modulation Technique

Enas Wahab Abood1, Abdulhssein M. Abdullah2, Mustafa A. Al Sibahee3,4, Zaid Ameen Abduljabbar5,6, Vincent Omollo Nyangaresi7, Saad Ahmad Ali Kalafy8, Mudhafar Jalil Jassim Ghrabta9 Department of Mathematics, College of Science, University of Basrah, Basrah, Iraq Department of Computer Science and Information Technology, University of Basrah, Basrah, Iraq Department of Computer Technology Engineering, Iraq University College, Basrah, Iraq College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China Computer Science Department, College of Education for Pure Sciences, University of Basrah, Basrah, Iraq Shenzhen Institute of Huazhong University of Science and Technology, Shenzhen, China Faculty of Biological & Physical Sciences, Tom Mboya University College, Homabay, Kenya Basra Oil Training Institute, Ministry of Oil, Basrah, Iraq Pharmacy Department, Ashur University College, Baghdad, Iraq

Audio steganography with enhanced LSB method for securing encrypted text with bit cycling

In this paper we presented a new approach to manipulate a digital signal in order to create a features array, which can be used as a signature to retrieve the signal. Each digital signal is associated with the local binary pattern (LBP) histogram; this histogram will be calculated based on LBP operator, then k-means clustering was used to generate the required features for each digital signal. The proposed method was implemented, tested and the obtained experimental results were analyzed. The results showed the flexibility and accuracy of the proposed method. Althoug different parameters of the digital signal were changed during implementation, the results obtained showed the robustness of the proposed method.

/pdf/developing-digital-signal-clustering-method-using-local-34ijncmsi8.pdf

Developing digital signal clustering method using local binary pattern histogram

In information transmission such as speech information, higher security and confidentiality are specially required. Therefore, data encryption is a pre-requisite for a secure communication system to protect such information from unauthorized access. A new algorithm for speech encryption is introduced in this paper. It depends on the quantum chaotic map and k-means clustering, which are employed in keys generation. Also, two stages of scrambling were used: the first relied on bits using the proposed algorithm (binary representation scrambling BiRS) and the second relied on k-means using the proposed algorithm (block representation scrambling BlRS). The objective test used statistical analysis measures (signal-to-noise-ratio, segmental signal-to-noise-ratio, frequency-weighted signal-to-noise ratio, correlation coefficient, log-likelihood ratio) applied to evaluate the proposed system. Via MATLAB simulations, it is shown that the proposed technique is secure, reliable and efficient to be implemented in secure speech communication, as well as also being characterized by high clarity of the recovered speech signal.

https://beei.org/index.php/EEI/article/download/2405/1897

A novel technique for speech encryption based on k-means clustering and quantum chaotic map

In this paper, a new technique that hides a secret text inside a speech signal without any apparent noise is presented. The technique for encoding the secret text is through first scrambling the text using Chaotic Map, then encoding the scraped text using the Zaslavsky map, and finally hiding the text by breaking the speech signal into blocks and using only half of each block with the LSB, K-means algorithms. The measures (SNR, PSNR, Correlation, SSIM, and MSE) are used on various speech files (“.WAV”), and various secret texts. We observed that the suggested technique offers high security (SNR, PSNR, Correlation, and SSIM) of an encrypted text with low error (MSE). This indicates that the noise level in the speech signal is very low and the speech purity is high, so the suggested method is effective for embedding encrypted text into speech files.

/pdf/hiding-text-in-speech-signal-using-k-means-lsb-techniques-2f3xg1epgv.pdf

Hiding text in speech signal using K-means, LSB techniques and chaotic maps

Medical images possess great privacy, as the patient's information must be completely confidential if it is transferred from one hospital to another via a hospital intranet or the internet to take medical consultations by specialized doctors. This paper presents a safe new method to transfer medical images by hiding them within a speech signal file, and this is done at three levels: First, a scrambling algorithm proposal to ensure a change in the original medical image based on the binary representation of the image values and using the Zaslavsky map, the second level is encryption the scrambled image relying on DNA coding and a series of keys generated by a proposed hybrid algorithm based on (Tinkerbelle map and 3D Henon) that provided us with good image distortion and provided difficulty in retrieving it by any intruder. The last level is to hide the contents of encrypted medical images in a speech signal depending on (integer wavelet transform and LSB algorithm), then using the proposed algorithm based on (fuzzy c-means clustering algorithm and short-time energy) to determine the locations of speech to hide in it. The results of this paper showed that using statistical measures of hiding and encryption were good in maintaining the confidentiality of medical image information compared to previous researches. Consequently, the use of encryption and hiding techniques together has provided double protection against the problems of malicious manipulation and privacy leakage on the internet as well as lack the hospital's intranet to security tools.

Hide Medical Images in a Speech Signal using DNA Coding and Fuzzy C-Means

Telemedicine applications allow the patient and doctor to communicate with each other through network services. Several medical image compression techniques have been suggested by researchers in the past years. This review paper offers a comparison of the algorithms and the performance by analysing three factors that influence the choice of compression algorithm, which are image quality, compression ratio, and compression speed. The results of previous research have shown that there is a need for effective algorithms for medical imaging without data loss, which is why the lossless compression process is used to compress medical records. Lossless compression, however, has minimal compression ratio efficiency. The way to get the optimum compression ratio is by segmentation of the image into region of interest (ROI) and non-ROI zones, where the power and time needed can be minimised due to the smaller scale. Recently, several researchers have been attempting to create hybrid compression algorithms by integrating different compression techniques to increase the efficiency of compression algorithms.

Iman Qays Abduljaleel

Papers

A novel technique for speech encryption based on k-means clustering and quantum chaotic map

Hiding text in speech signal using K-means, LSB techniques and chaotic maps

Hide Medical Images in a Speech Signal using DNA Coding and Fuzzy C-Means

Significant medical image compression techniques: a review