Desorption/ionization on silicon (DIOS) mass spectra of model ionic dyes methylene blue (MB+Cl-) and methyl orange (Na+MO-) were studied using p+ type-derived porous silicon (PS) free layers. As-prepared PS (PS-H), the PS thermally oxidized at 300 degrees C (PS-OX), PS with chemically grafted cation-exchanging alkylsulfonic acid (PS-SO(3)H) and anion-exchanging propyl-octadecyldimethylammonium chloride (PS-ODMA+Cl-) groups was tested as ionization platforms. Two mechanisms of the methylene blue desorption/ionization were found: (1) the formation of [MB + H]+* ion due to the reduction/protonation of MB+, which is predominant for PS-H and PS-OX platforms and (2) direct thermal desorption of the MB+ cation, prevailing for PS-SO3H. The fragmentation of the cation is significantly suppressed in the latter case. The samples of PS-SO3H and PS-ODMA+ Cl- efficiently adsorb the dyes of the opposite charge from their solutions via the ion-exchange. Consequent DIOS MS studies allow to detect only low fragmented ions (MB+ and MO-, respectively), demonstrating the potential of the ion-exchange adsorption combined with DIOS MS for the analysis of ionic organic compounds in solutions.

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The developed method of steganographic hiding of text information in an audio signal based on the wavelet transform acquires a deep meaning in the conditions of the use by an attacker of deliberate unauthorized manipulations with a steganocoded audio signal to distort the text information embedded in it. Thus, increasing the robustness of the stego-system by compressing the steganocoded audio signal subject to the preservation of the integrity of text information, taking into account the features of the psychophysiological model of sound perception, is the main objective of this scientific research. The task of this scientific research is effectively solved using a multilevel discrete wavelet transform using adaptive block normalization of text information with subsequent recursive embedding in the low-frequency component of the audio signal and further scalar product of the obtained coefficients with the Daubechies wavelet filters. The results of the obtained experimental studies confirm the hypothesis, namely that it is proposed to use recursive embedding in the low-frequency component (approximating wavelet coefficients) followed by their scalar product with wavelet filters at each level of the wavelet decomposition, which will increase the average power of hidden data. It should be noted that upon analyzing the existing method, which is based on embedding text information in the high-frequency component (detailed wavelet coefficients), at the last level of the wavelet decomposition, we obtained the limit CR = 6, and in the developed, CR = 20, with full integrity of the text information in both cases. Therefore, the resistance of the stego-system is increased by 3.3 times to deliberate or passive compression of the audio signal in order to distort the embedded text information.

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