This paper throws light on chaotic shift keying-based speech encryption and decryption method. In this method, the input speech signals are sampled and its values are segmented into four levels, namely L 0 , L 1 , L 2 , and L 3 . Each level of sampled values is permuted using four chaotic generators such as logistic map, tent map, quadratic map, and Bernoulli's map. A chaotic shift keying mechanism assigns logistic map for L 0 , tent map for L 1 , quadratic map for L 2 , and Bernoulli's map for L 3 for shuffling the speech samples at every level. Further, the sampled values are permuted using Chen map which uncovers the chaotic behavior. Various testing methods are applied to analyze the efficiency of the system. The results prove that the proposed system is highly secured against the attackers and possesses a powerful diffusion and confusion mechanism for better speech communication in the field of telecommunication.

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The present work proposes two novel approaches namely One Dimensional adaptive average Local Binary Pattern (1-D AaLBP) and One-Dimensional adaptive difference Local Binary Pattern (1-D AdLBP) for feature extraction from EEG signals and Convolutional Neural Network (CNN) for classification of EEG signals. Both the proposed feature extraction methods are computationally easy to implement. In the first step the histograms are formed from the extracted patterns, after that feature vectors of the histogram are given as input to the classifier. Two benchmark EEG datasets such as Bonn and CHB-MIT are employed for conducting experiments for comparing the performances of the proposed method with other existing research works. The performance measures such as sensitivity, specificity, classification accuracy and execution time are used for evaluating the proposed methods. It is learned from the experiments conducted that among various methods the proposed method provides improved performance in terms of sensitivity, specificity, classification accuracy and execution time.

The attempts to improve the security of the speech signals are increasing with new encryption schemes. Many recent researches of speech encryption algorithms have been increasingly based on chaotic systems, but the drawbacks of weak security and small key space in one-dimensional chaotic cryptosystems are conspicuous. In this article, a new speech encryption scheme is used. It employs one of the three-dimensional chaotic systems to encrypt a source signal by permutations, thereby confusing the relationship between the cipher signal and the plain signal. A higher-order polynomial equation and rotating matrix are used to strengthen the proposed method. It significantly increases the resistance to attacks. The proposed system has the advantages of smaller iteration times and bigger key space. The system has entertained high-security analysis such as the signal-to-noise ratio, peak signal-to-noise ratio, auto correlation, key sensitivity analysis, number of sample change rate, unified average changing intensity, and histogram analysis. The analysis results illustrate that the proposed system is highly efficient and robust to threats.