AUTOMATIC CONTROL AND COMPUTER SCIENCES最新文献

In light of the rapid development of edge computing and the increase in the number of connected devices, this paper addresses the pressing issue of ensuring data integrity. The main focus is on the use of blockchain technology, which offers unique opportunities to solve this problem. This paper provides a brief overview of the existing methods and a new method for ensuring integrity based on blockchain technology. It is proposed to use the Hot Stuff consensus algorithm in the case of multiple active nodes, which ensures fast operation and scalability of the system. Particular attention is paid to the use of a secondary blockchain based on Ethereum to provide additional security and create checkpoints in large blockchain networks. This makes it possible to simplify the work of edge servers and ensure data integrity verification upon the user’s request using smart contracts. The proposed new approaches to ensure data integrity and use blockchain technology can be applied not only in the field of edge computing but also in various variations of the Internet of Things.

Mathematical models are proposed for protecting an information system (IS) from information security threats (ISTs) based on the classical model of the struggle between two opponents: the Lanchester model. Using the method of constructing systems of differential equations with the given set of invariants—first integrals—a deterministic model with invariant control and a stochastic model with Wiener perturbations, a model with programmed control with a probability 1, are constructed. The behavior of systems is assessed using mathematical modeling in the MathCad environment. The behavior of the constructed models depending on the initial conditions is considered. The existence of a stochastic model of protection of an IS from ISTs, protected with a probability 1, is established.

This article presents the main probability-theoretic models that describe a wide class of physical random number generators and allow us to propose general approaches to their synthesis and analysis.

The modern trend of increasing labor productivity and business process efficiency entails the optimization of software development processes through the use of generative artificial intelligence models trained on various code bases and manual copying of code fragments. Given the growing number of registered vulnerabilities, methods for detecting clones of the software code are needed. A method for assessing the similarity of fragments of the program code of binary executable files, which is based on the representation of the code in the form of an FA-AAST tree and the apparatus of graph neural networks, is proposed. The results obtained during testing on open and closed source software demonstrate the correctness of the proposed method and higher accuracy compared to the solutions considered.

The problems of using mobile devices in the work process of an organization when applying the BYOD concept are analyzed. An adapted methodology for assessing security threats is proposed for BYOD concepts. As a supplement to the traditional approach to building a system for ensuring information security in a corporate information system based on BYOD, a software tool for controlling unauthorized access to mobile devices is developed and tested.

Ensuring consistent access control is one of the key security challenges in heterogeneous big data systems. The problem is the large number of data processing tools, as well as sources and users of information; heterogeneity of security models; and complexity of granular access rules. Analysis of the time factor in this case will improve the consistency and reliability of access control. The aim of this study is to select a methodology and tools for implementing temporal logic in the processes of access control verification of big data systems. The types of temporal logic and verification methods based on the temporal logic of actions (TLAs) are analyzed. The use of TLA+ is proposed to solve the given problem and an example of the corresponding specification is given.

This paper studies an approach to counteract network attacks based on network reconfiguration to eliminate the possibility of the successful completion of an attack by an intruder. To implement this approach, it is proposed to use a recommender system mechanism that provides both the generation of possible network topologies and their ranking. The proposed intelligent recommendation system is based on a reinforcement learning algorithm based on the actor-critic model. The conducted experimental studies confirm the effectiveness of the developed system.

A mathematical model for data representation is developed for use in automated security analysis systems. The model allows linking information about the system obtained by a specialist during the security analysis process with the set of attack scenarios in which they may be involved. Each time a scenario is applied, new information emerges, which helps expand the attack graph.

An approach using a generative adversarial network (GAN) is proposed to increase the robustness of the steganographic method against modern steganalyzers. This approach is based on the combined operation of a GAN, a pixel importance map, and the least significant bit (LSB) substitution method. The results of the experimental studies confirmed the effectiveness of the proposed approach.

Among the post-quantum algorithms selected by the National Institute of Standards and Technology (NIST) for standardization, the main mathematical apparatus is the mechanism of algebraic lattices, while the apparatus of hash functions is an alternative. Unlike isogenies of elliptic curves, these mechanisms use larger sizes of both public keys and signatures. Using the example of a multiple signature protocol based on isogenies of elliptic curves, we will show how, using the masking method, we can protect against the main attack on the given device, while obtaining a smaller signature size.