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We present four encryption approaches for voice communication systems by combining Arnold cat map with either Henon or modified Henon or Unified or Lorenz chaotic maps. These approaches depend on permuting and substituting voice samples using transform domains and secret keys in time. We use two levels of chaotic maps to increase the security of th...
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... The process of encryption is complete through cat map iteration, after execution M iterations, there are T integers that are positive such that (X n+1 , Y n+1 ) = (X n , Y n ). The parameters A, B, and the size of the sample's matrix (N × N matrix) all affect the time [20] -2D Duffing Map: A discrete-time dynamical system that displays chaotic behavior is the Duffing map [32]. -After taking a point (Xi, Yi) off the plane, the 2D Duffing map maps a new point [33]. ...
In cloud computing, resources are used to communicate instead of local servers or individual devices. However, sharing resources among several users is a difficult issue in cloud communication. Cryptography and steganography techniques are used for cloud storage to address data security challenges. This paper presents a novel method for securely encrypting image data for transmission and link exchange with a cloud storage service. There are two phases to accomplish the encryption process, the first phase encrypts the image file by XORing it with a random key that is generated by a new hybrid of the chaotic map. The second phase converts the encrypted image format to audio format to add another layer of security and improve secure image data transfer. The random key is generated using a hybrid chaotic map and has the benefit of having more than 10256 key spaces and the necessary level of security. Based on a statistical analysis of the encryption, the quality of the image is evaluated using several criteria, and the results demonstrate the algorithm's ability to accomplish resist encryption
... Content-based encrypted speech retrieval model can be divided into encryption, feature extraction, and retrieval. The encryption algorithms include chaotic map encryption [6], time-frequency domain scrambling encryption [12], AES encryption [13], homomorphic encryption [8], etc., which make the speech signal loses most of its perceptual characteristics by performing operations such as scrambling, diffusion, and XOR on the speech signal to guarantee the security of speech data. Generally, features are mainly extracted from the time domain, frequency domain, and transform domain, because the human cochlea is more sensitive to sound frequency, transform domain and frequency domain features are more robust than time domain features. ...
In order to improve the impact of noise on the robustness and discrimination of the speech perceptual hashing scheme, improve retrieval efficiency and retrieval accuracy, and protect the privacy of the cloud speech data, a retrieval method for encrypted speech based on improved power normalized cepstrum coefficients (PNCC) and perceptual hashing was proposed in the paper. Firstly, the original speech was encrypted by Henon chaotic map inter-frame scrambling encryption algorithm before uploading to the encrypted speech library in cloud server. Secondly, the discrete wavelet transform (DWT) and first-order difference coefficient were used to improve the PNCC feature extraction algorithm to extract speech features, and the principal component analysis (PCA) was used to reduce high-dimensional audio features to one dimension to form frame features that can represent the speech segment. Finally, the frame features are constructed as binary hashing sequences using hash functions and upload it to the system hashing index table in the cloud. When the user retrieves, the hashing sequence of query speech is extracted and matched with the encrypted speech features by normalized hamming distance in the cloud system hashing index table to obtain the retrieval result. Experimental results show that compared with the existing methods, the proposed method has good robustness and discrimination, and improves retrieval efficiency and retrieval accuracy, the security of cloud speech data is improved. In addition, the proposed method has good recognition ability under simulated real noise environment.
... Arnold's cat map is commonly used for image encryption by shuffling the image pixels but actually it can be used to encrypt other form of multimedia data. In [11] and [12], there are good examples of audio encryption using Arnold's cat map for securing voice communication. Arnold's cat map can also be used to watermark an image or video, which is useful for tamper detection. ...
... In [3], E. Mosa et al. implemented a voice encryption method based on permutation of voice segments using a 2D chaotic map (Baker map) and substitution using masks in time and transform domains. In [8], Arnold cat map was applied by Mahmoud F. Abd Elzaher and others to permute voice samples, then either Henon or modified Henon or Unified or Lorenz chaotic systems were applied to produce the mask key and thus replace the permuted samples. In previous research www.ijacsa.thesai.org ...
... The Lorenz Chaotic map system is a three-equation scheme. The Lorenz system equations are defined as in Formula (1) [6,7,8,9,10]. ...
Here, a proposed voice scrambling algorithm established on one of two 3D chaotic maps systems (VSA3DCS) will be presented, discussed, and applied on audio signals file. The two 3D chaotic map systems in which any one of them is used to build VSA3DCS are Chen's chaotic map system and Lorenz chaotic map system. Also Arnold cat map-based scrambling algorithm will be applied on the same sample of audio signals. These Scrambling algorithms are used to encrypt the audio files by shuffling the positions of signals at different conditions with the audio file as one block or two blocks. Amplitude values of audio signals with signals' time are registered and plotted for original file versus encrypted files which are produced from applying VSA3DCS using Chen's, VSA3DCS using Lorenz, and Arnold-based algorithm. The spectrogram frequencies of audio signals with signals' time are plotted for original file versus encrypted files for all algorithms. Also, the histogram of the original file and encrypted audio signals are registered and plotted. The comparative analysis is presented by using some measuring factors for both of encryption and decryption processes, such as; the time of encryption and decryption, Correlation Coefficient of original and encrypted signals between the samples, the Spectral Distortion (SD) measure, Log-Likelihood Ratio (LLR) measure, and key sensitivity measuring factor. The results of several experimental and comparative analyses will show that the VSA3DCS algorithm using Chen's or Lorenz is a good algorithm to provide an effective and safe solution to voice signal encryption, and also VSA3DCS algorithm better than Arnold-based algorithm in all results with all cases.
The popularity of social media websites tends to boost the volume of multimedia material. This results in the development of the brand-new industry known as the Multimedia Internet of Things. Lightweight image encryption methods are required to protect multimedia data on these resource-constrained devices. Since chaos theory has grown more common in modern multimedia cryptography, it serves as the foundation for the suggested lightweight encryption technique. 2D augmentation models are used in this chaotic-based multimedia encryption method to provide secure data transit. The suggested method has minimum residual clarity and key sensitivity while, simultaneously maintaining the excellent encryption quality of chaotic maps. The simplified image encryption technique employs the chaotic map model, which has the properties of confusion and diffusion. We have also put forth a novel key generation algorithm for use with the Logistic map and the Rubik’s cube transformation. Using the Elliptic-Curve Cryptography (ECC) Key Algorithm, the initial values are produced. To analyze the computational complexity, the suggested method is applied to medical (binary) and colored images. The histograms of the encrypted images are flat and distributed across all the pixel values, according to the security analysis. These images have an entropy of 7.86046675 with average correlation values of 0.0010575 (horizontal), 0.013994 (vertical), and 0.00235 (diagonal) (encrypted image). The suggested lightweight image encryption hence displays a high level of security.
