The article considers the impact of redundancy on the security of technical information leakage channels and the approximate correction of the error probability in the channel in the absence of information about the origin of redundancy. The mechanisms of introducing redundancy into signals are investigated, which contribute to improving noise immunity by correcting errors, but also create risks of reducing the confidentiality of transmitted information. The article considers two main types of redundancy: artificial, which is formed through coding and control characters, and natural, which is a consequence of the peculiarities of the information source. The principles of its decoding differ significantly. This makes it impossible to directly apply error probability correction methods developed for artificial redundancy to natural redundancy. Artificial redundancy has a clear structure and is used to increase noise immunity, while natural redundancy arises from the characteristics of the information source, manifesting itself through correlations between symbols, repeated patterns and statistical regularities. The article considers the features of speech and visual channels, where natural redundancy plays a key role in error correction. In speech channels, it helps to increase the reliability of information reception due to the subjectivity of pronunciation and perception, and in visual channels - due to the regularity of pixel distribution in images. A new approach to decoding based on the ordering of code combinations by weight is proposed. The method of dividing possible 7-bit combinations into groups is used, which provides more efficient error correction. The traditional approach to error correction in the Hamming (7,4) code and its limitations at high levels of interference are also considered. The results obtained can be used to improve methods of increasing the reliability of data transmission and reducing the risks of information leakage through technical channels. Importantly, this method not only improves error correction, but also opens up new opportunities for adaptive coding in complex information transmission conditions. Its versatility makes it possible to apply the approach in various fields, from digital communications to speech signal processing.
Ivanchenko et al. (Tue,) studied this question.
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