Audio encryption based on the cosine number transform

Abstract

In this paper, we introduce an audio encryption scheme based on the cosine number transform (CNT). The transform, which is defined over a finite field, is recursively applied to blocks of samples of a noncompressed digital audio signal. The blocks are selected using a simple overlapping rule, which provides diffusion of the ciphered data to all processed blocks. A secret-key is used to specify the number of times the transform is applied to each one of such blocks. Computer experiments are carried out and security aspects of the proposed scheme are discussed. Our analysis indicates that the method meets the main security requirements of secret-key cryptography. More specifically, after the encryption of 16-bit audio signals, correlation coefficients significantly close to 0 and entropy values close to 16 were obtained. Furthermore, the flexibility of the method easily allows key space sizes greater than 2 256 and provides robustness against differential, known-plaintext and chosen-plaintext attacks.

Speech encryption using chaotic shift keying for secured speech communication

“…In Table 3, the minimum, maximum, and average values of NSCR and UACI, computed from the encryption of four different modified versions of each speech signal are given. The results are considerably close to the ideal values and independent on the position of the modified sample as compared with [25].…”

“…Actual and modified speech signals are encrypted using the same key, and two ciphered speech signals are generated. These ciphered speech signals are then compared by the number of sample change rate (NSCR) and the unified average changing intensity (UACI) [25]. The NSCR is given by NSCR and UACI are 100% and 33.3%.…”

Spreading-Based Voice Encryption by Means of OVSF Codes

“…Likewise, the proposed scheme presented a null correlation between the original and encrypted signal, and consequently the scheme presented a low probability against statistical attacks. Not given 0.000236 Not given [10] 3.4 × 10 80 Not given −0.000198 Not given [20] 2 256 Not given 0.002000 Not given [12] ( In terms of computational cost in the recovery process, the proposed approach was compared to a similar method using variable length codes obtained through a binarization process based on the Collatz Conjecture [12]. For this comparison, all 85 test signals were used, coded, and then decoded.…”

Blind Audio Watermarking Technique Based on Two Dimensional Cellular Automata

“…Many audio scrambling schemes were proposed in literature, such as scrambling based on Arnold transform [18], Imitation [19] and cosine number transform [20]. An interesting work that is already applied in watermarking is the work done in [21] and [22], where the authors propose changing the dimensions to address the problems in onedimensional linear mapping.…”