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After the tremendous development and fast growth in communication systems and electronic devices, information security and preservation have become one of the most important procedures to be considered when transferring data between two parties. Encryption and data hiding are two of the most important techniques to protect the information sent over networks and the Internet. In this paper, a new technique of encryption and concealment is used through the following steps: First, the secret information is encrypted by using developed DNA to get (S1), second, by scrambling the encrypted data, the (S1) is diffused by using a zigzag method to get (S2), third, re-obfuscation the (S2) by using developed zigzag method through using Tinkerbell technique to get (S3), fourth, perform XoR operation between the (S3) and the Tinkerbell technique to get (S4), and fifth, the (S4) is hidden in the random locations of the cover image based on the LSB technique and the Tinkerbell technology, where the Tinkerbell has incredibly excellent characteristics and used to generate random sequence numbers twice with different initial and parameters value, once for the encryption process for scrambling secret information and once for the hiding process for determining hidden locations. Several metrics were used to evaluate the system's efficiency: histogram, PSNR, MSE, mean absolute error, bit error rate, encryption quality, Unified Average Changing Intensity, hamming distance, entropy, and correlation coefficient. The experimental results display that the suggested method has a good performance and reliability, high security, and greater embedding capacity and ensures higher image quality; also, the proposed method presented preferable outcomes when compared to other approaches. [ABSTRACT FROM AUTHOR]

To improve the imperceptibility without decreasing the steganographic capacity when steganography by a modification to an audio is carried out, this paper proposes an optimal matching path algorithm to reduce the modification to achieve it. A steganography operation unit is defined, which is composed of every N consecutive audio frames and each frame includes M LPC parameters. All these parameters in the same steganography operation unit will form an M × N matrix. A traversal path is a sequence of all these parameters in the matrix. Each parameter in the matrix will be converted into a one-bit binary digit based on two subcodebooks divided by the complementary neighbor vertex (CNV) method. Thus, every traversal path will have a corresponding binary string named PathBinStr. Steganography is performed by computing the Hamming distance between the binary secret and the corresponding PathBinStr and selecting the traversal path with minimal hamming distance expected value to hide the secret via the CNV embedding method. The experimental results show that the proposed steganography algorithm has better performance in audio quality and the modified bit rate decreases from 50 to 37.4% when only 6 traversal paths are predefined, and its processing time can satisfy the real-time requirement of VoIP services. Also, it does not change the audio size, and the theoretical analysis and experiments show its undetectability is good. [ABSTRACT FROM AUTHOR]

In this paper, a steganography–steganalysis model for quantum audio signals is presented. This model consists of two separate parts of steganography and steganalysis. In the steganography part, to increase the imperceptibility and enhance the undetectability of the least significant bit method, first, the quantum host audio signal is divided into quantum frames of the specified length, and then, using the triangular number sequence, some samples of each frame are selected for the embedding operation. Finally, the embedding process is carried out within the least significant fractional qubit of the amplitude information of the selected samples. The steganalysis part also includes a quantum universal steganalyzer for detecting the embedding operations of the steganography part and a feature extraction module for calculating the power feature of quantum audio signal frames. The recognition operation is based on the quantum K-nearest neighbor algorithm and the Hamming distance criterion. All quantum circuits of the steganography and steganalysis parts of the proposed model were simulated and then tested and evaluated using different audio files. Detection accuracy of over 90% indicates the accuracy and efficiency of the proposed method in quantum audio steganography detection in the context of quantum communication networks. [ABSTRACT FROM AUTHOR]

Compared with Boolean functions, multi-output Boolean functions (a.k.a. vectorial Boolean functions) are commonly used in classical cryptography. More generally, many cryptographic primitives can be treated as multi-output Boolean functions. Hence, the research on property testing of multi-output Boolean functions is meaningful for the design and cryptanalysis of symmetric cryptography. This paper mainly focuses on the cryptographic property testing of multi-output Boolean functions in the quantum world. Firstly, the generalized Deutsch–Jozsa algorithm is proposed to distinguish balanced multi-output Boolean functions from constant ones with a single query. This algorithm has a wider scope of applications with arbitrary ancillary inputs. The first generalized Bernstein–Vazirani algorithm suitable for multi-output Boolean functions is presented to recover the linear coefficients of linear functions. Then, combined with the generalized Deutsch–Jozsa algorithm, the quantum algorithm for estimating Walsh coefficients of multi-output Boolean functions is proposed with the same idea of quantum approximate counting algorithm, accompanied with an algorithm for computing the Walsh coefficient at a specified point based on quantum exact counting algorithm. Finally, with the usage of algorithms mentioned above, the cryptographic property testing of multi-output Boolean functions is studied. In order to describe the distances from having the certain properties, Euclidean distance and Manhattan distance are introduced as complements of Hamming distance. According to the definition, the first balance testing of multi-output Boolean functions is presented by testing the uniformity of images. The second algorithm exploits the relationship between balance and the Walsh coefficients at the point 0 which could be easily extended to k-order resiliency testing. We also briefly analyze the query complexities of strict avalanche criterion testing and k-order propagation criteria testing. The linearity testing algorithm for multi-output Boolean functions based on the generalized Bernstein–Vazirani algorithm can be adapted to Boolean functions achieving a further speedup. The non-junta testing algorithm is proposed with lower query complexity. [ABSTRACT FROM AUTHOR]