# Secure Speech Content Based on Scrambling and Adaptive Hiding
## 1 Introduction  
In the last decades, technological development has highly facilitated communication processes between users, allowing a free flow of information of any kind (i.e., text, image, audio, video, etc.). However, in many cases, confidentiality of information can be a major factor to satisfy. In the case of audio signals, with the purpose of preserving confidentiality, there are three solutions available for covert communication: (i) To encrypt transmitted information, (ii) to manipulate or alter content (scrambling), (iii) to transmit secret information within another signal. In the first two cases, a third unauthorised party can infer that sensitive information is being transmitted, but is ignorant of its content. In the third case, even if the third party intercepts the information being transmitted, the secret content goes unnoticed. Consequently, if the voice signal is transformed through scrambling or encryption, and the result hides in a host signal, the final system will work with at least two levels of security. In the specific case of techniques applied to voice messages, there are works in the area of data hiding (specifically steganography) and in the area of data randomisation (scrambling). In both scenarios, the process can use a secret key to increase system security. Only the authorised user who has the correct secret key will be able to reverse the concealment process and to obtain the original voice message. Techniques of data concealment generally consist in inserting the information to be transmitted within some other content. To do so, various multimedia signals such as audio [1], text, video [2] or image [3; 4] signals, can act as a host that carries secret information. The expression \"hiding\" can be interpreted as secretly keeping the existence of information (steganography) or making it imperceptible (watermarking). With regard to steganography, its objective is to make the secret information invisible by hiding it, whereas watermarking is based on the necessity to protect the content's author copyright. In steganography, the most important design criteria are transparency and imperceptibility; in watermarking, robustness is the main criterion to satisfy. The state-of-the-art of steganography techniques include temporal domain [5], frequency [6; 7] or time-frequency [6; 8] that are based on masking [8; 9; 10] or substitution. However, most schemes work with low hiding rates, thus the duration of the secret message is very short. In scrambling, there are techniques based on permutation in the time domain [11; 12] or frequency [13; 14] domain. The main weaknesses of these kind of methods are related to residual intelligibility and key robustness against attacks. Additionally, many schemes do not guarantee unconditional security, it means that with enough resources (i.e., time, hardware), the key is decipherable. Covert communication techniques based on Artificial Intelligence (AI) techniques that satisfy the unconditional security encompass, among others, cellular automata (CA) [15; 16], genetic algorithms (GA) [17], and imitation [12]. In the case of the cellular automata technique [10], a CA is used to generate a key as long as the secret message, so that mapping is one to one. Every time the system is executed, a different key is generated, and all keys are equally probable; as a result, if an intruder intercepts the hidden message, he/she has no certainty of which key has been selected, and in turn, he/she cannot decipher the secret voice message it contains. The disadvantage of the previous proposal lies in the system not guaranteeing low residual intelligibility; in other words, for certain keys some remnants of the original voice message may remain in the concealed voice message. In the group of genetic algorithms, the GA is used to select the less significant bits (LSB) to hide the encrypted content [17]. The disadvantage is the sensitivity to the cost function.