Analysis of the Problems of Using Steganographic Methods in Implementing Illegal Actions and Their Role in Digital Forensics

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS
S. V. Bezzateev, M. Yu. Fedosenko
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引用次数: 0

Abstract

This paper is a study of the problem of the use of steganographic algorithms by attackers to hide and exchange illegal data. The paper formulates the relevance of the problem by analyzing cases of using steganography in attacks on computer systems and based on the trend of developing a controlled Internet, supported by a regulatory framework. This article presents an analysis of methods for hiding data and their subsequent exchange on public internet resources through a review of the works of researchers in this area; and the main tools used by attackers are identified and described. As an analysis of counteraction methods, a comparative characteristic of the use of various artificial intelligence technologies in the field of steganalysis is presented; the most promising ones applicable for the tasks of the automatic analysis of content posted on public internet resources are highlighted. As a final provision of the work, the process of exchanging hidden data by intruders using EPC notation is modeled; the directions and tasks of steganalysis, whose solution will allow developing a unified system to protect public internet resources in the future, are highlighted; and the prospects for using new steganographic algorithms, such as hiding in the blockchain and the source code of resources, as well as posting content with the presence of physical information attachments, are presented.

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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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