| Abstrakt: |
It is obvious that there can be no security without information security. Staying in one or another in formation space changes consciousness, forces people to commit crimes of varying degrees of severity, or to justify supporting criminals. An important tool in the violation of information security is propaganda, which does not disdain any methods to achieve the goal, including using fake photo, video, and audio files to realize informational and psychological influence on society. The methods of dealing with such cases are comprehensive and complex in nature. Among them, the methods of establishing the truth of digital content or proving that this or that in formation is fake play an important role. When forging digital files, in particular, digital images, post-processing methods such as blurring, multiplicative noise, etc. are often used. Identifying these types of post-processing is currently not a solved task, although it has certain successes. The purpose of this work is to improve the detection efficiency of digital image processing by developing a blur detection method and a multiplicative noise detection method. A computational experiment was conducted, as a result of which it was established that the discrete cosine transformation is a convenient and effective tool for detecting Gaussian blur and multiplicative noise. Blur ring reduces the value of high-frequency DCP coefficients, while multiplicative noise increases them. At the same time, the raw image has high-frequency coefficients within a certain norm. In the work, it was possible to single out threshold values that allow recording deviations from the norm in one direction or another, on the basis of which a method for detecting blur ring and a method for detecting multiplicative noise, based on the analysis of high-frequency coefficients of DCP, was developed. [ABSTRACT FROM AUTHOR] |
