The access control mechanism is the basis for ensuring the security of system software (OS or DBMS). In accordance with the requirements of regulatory documents of domestic regulators for certified information security tools, as a scientific basis for the implementation of such a mechanism, a formal access control model that meets the GOST R 59453.1-2021 criteria should be developed. Such a formal model for the Astra Linux operating system certified for the highest protection classes and assurance levels is the mandatory entity-role model of access and information flows security control in OS of Linux family (MROSL DP-model). Taking into account the introduction of new elements into the access control mechanism of the Astra Linux and in order to ensure a more accurate correspondence of the model description to this mechanism, the development of scientifically based technologies and practices for the development and verification of formal models, the MROSL DP-model is regularly revised. Another such revision of the model now has been completed for two levels of its hierarchical representation, corresponding to role-based access control (representing discretionary access control, traditional for the OS of Linux family) and mandatory integrity control, reflecting the most significant changes in the Astra Linux release 2023. The article analyzes the main results of this revision, within which: functions that define new entity labels are introduced, the composition and descriptions of the de-jure rules for transforming system states, administrative and negative roles are changed, the wording is corrected and several statements are re-proved, and other changes are made in the model description.

Confidentiality is an important security feature when exchanging data over a network. To implement it, a family of SSL/TLS protocols is used, which, however, do not fully hide either the visited site or the user's actions. In addition to privacy, privacy also plays a significant role for network users. To provide additional privacy, some software solutions have been implemented, such as Tor and I2P. As a measure of the privacy of the relevant solutions, their resistance to a specialized class of attacks can be used. One of the attacks is Website Fingerprinting, which allows the traffic sent and received by a known user to determine which sites he visited. Website Fingerprinting is a classification task, where the object is the user's visit to the website, and the class is the website itself. This article examines the Website Fingerprinting attack for HTTP/2 traffic. The paper contains a description and calculation of popular features used in traffic classification, and assesses their applicability to the Website Fingerprinting task. To implement the Website Fingerprinting attack, several classifiers are built, among which an algorithm is selected that gives the best result on the collected data set. The accuracy of the best classifier is 97.8% under certain assumptions. In addition, there is an assessment and analysis of some real-world constraints affecting the accuracy of classification.

The article examines the well-known cryptographic problem of obtaining data from a database by a client so that no one with access to the server except the client himself could obtain information about this request. This problem known as PIR (Private Information Retrieval) was formulated in 1995 by Chor, Goldreich, Kushilevitz and Sudan in the information-theoretic setting. A model of cloud computing is proposed. It includes a cloud, an authentication center, a user, clients, trusted dealer, an active adversary executing the protocol in the cloud. The attacking side has the ability to create fake clients to generate an unlimited number of requests. An algorithm for the organization and database distribution on the cloud and an algorithm for obtaining the required bit were proposed. An injective transformation of bit numbers represented in the l-ary number system by words of length d into words without repeating digits of the same length with an alphabet of 𝒍̂ digits is used, i.e. a transformation {0, ..., l}^d →{0, ..., 𝒍̂}^d was constructed. This transformation reduces the probability of disclosure of the requested bit number. The communication complexity and probability of revealing required bit were estimated, taking into account the performed transformation.

Fuzzing of JavaScript engines is one of the most difficult areas in web-browser testing due to the complexity of input data generating. JavaScript engines process JavaScript code on a web page and require constant support for new language standards and increasing complexity in their architecture. The most common fuzzers today are not able to effectively mutate complexly structured input data during fuzzing. Generating JavaScript code from scratch does not allow encapsulating the necessary semantics, and current mutators quickly destroy the syntax and semantics of the input data language. This article presents a new mutation strategy that preserves the syntax and semantics of the input data by modifying the AST of JavaScript code fragments. This method allows you to efficiently generate diverse and correct input data, which can lead to the identification of errors and vulnerabilities in JavaScript engines. This method can be used to improve the security of web browsers and ensure reliable interpretation of JavaScript code.

The paper analyzes the existing methods to optimize the time costs and increase the accuracy of calculations in the high-level simulation of networks-on-chip. The description of parameters and characteristics of networks-on-chip calculated by different models is given, and their influence on the speed of high-level simulation is analyzed. Adaptation of existing methods of modeling optimization for implementation in the system of automation of networks-on-chip design is carried out.

This paper presents an open-source software for generation, storage, and analysis of combinational circuits. The previously created methods for generating combinational circuits have been optimized, and a dataset has been formed. The generation of combinational circuits is carried out on various devices. The application implements the possibility to combine the generated datasets into a single storage (Synology Drive), as well as analyze the fault tolerance of combinational circuits using various methods for their evaluation. New possible methods for assessing combinational circuits’ reliability using machine learning are proposed.

The boundary element method usage for the numerical simulation in continuum mechanics problems leads to the need to solve a system of linear algebraic equations with a dense matrix. The de facto standards for the interface of functions over dense matrices and vectors software implementations are BLAS/LAPACK. Among the optimized open-source BLAS/LAPACK implementations, only the OpenBLAS library includes optimizations for the widest range of hardware platforms. This library is optimized for Intel, AMD, ARM and RISC-V architectures. The open RISC-V architecture ecosystem is currently actively developing. European supercomputing centers have opened RISC-V competence centers as part of the government's EuroHPC grant support, since solutions based on the ARM architecture are not recognized as part of the European initiative to develop its own technological independence. Currently, companies included in the international RISC-V consortium are developing not only high-performance RISC-V processors, but also AI accelerators, as well as video cards based on RISC-V architecture. OpenBLAS is actively supported and optimized for emerging RISC-V hardware and extensions. However, libraries used in product code are traditionally subject to strict requirements for stability and reliability in order to minimize possible errors and failures in the product. As it turned out, from this point of view, OpenBLAS has a number of problems that we had to solve in order to productize this library. In this article the OpenBLAS test system is described, the problems of testing the LAPACK functionality of the library and ways to solve them are discussed. In addition, the test coverage of the BLAS functionality is analyzed and the results achieved in increasing it are presented. It is planned to contribute the described changes to the OpenBLAS project.

This paper focuses on the development of trusted tools for designing digital circuits in the basis of heterogeneous field programmable gate arrays (FPGAs). Designing heterogeneous FPGAs is one of the most actively growing areas in Russian microelectronics at present. The paper discusses the main problems and challenges associated with the development of trusted computer-aided design tools. The authors propose a relevant approach to the development of a computer-aided design system based on the use of open-source software tools together with proprietary developments for its critical components. This approach allows to increase the efficiency and reliability of the design process in the basis of heterogeneous FPGAs. The paper considers such stages of the design flow in the basis of heterogeneous FPGAs as logic synthesis and technology mapping, different stages of layout synthesis and static timing analysis. The work is of interest to specialists in the field of microelectronics, as well as to researchers involved in the development of IC design tools and systems. The research results contribute to the improvement of existing IC design methods and tools, as well as to the development and expansion of the Russian electronic component base.

As part of the ICCAD Contest 2023 (Problem C) competition, the paper describes a methodology for applying ML models to perform static IR drop analysis. Methods for obtaining a database for training a neural network to solve this problem are given. We consider a technique for training an ML model to analyze the static IR-drop effect. The generation of input data for training a neural network from SPICE netlists is also discussed in this paper. This solution is ranked in the TOP 3 at the ICCAD Contest 2023 competition.

The paper explores the possibilities of using neural network methods to solve the problem of global routing for VLSI ASIC design. An algorithm has been developed for generating a training dataset based on the Lee algorithm, which allows one to synthesize three-dimensional matrices with obstacles and points that need to be connected. The U-Net fully convolutional neural network, effective for semantic segmentation of images, was selected for training. The quality of the results was assessed using a validation data. A significant reduction in routing time compared to the Lee algorithm was shown, but the share of unbroken routes was only 37%. Ways to improve the training dataset and adapt the approach to real conditions using DEF and GUIDE files are proposed. In general, the work demonstrated the potential of neural network methods to speed up the global routing task, but continued research is required to improve the quality and reliability of the results. The work is useful for specialists in the field of integrated circuit design and machine learning.

Residue number systems find wide application in cryptography, digital and image signal processing, and other domains necessitating division operations. Nevertheless, division is the most computationally intensive activity in residue number systems. An optimized division algorithm based on the Akushsky core function is presented in this paper. The suggested method exhibits superior computational efficiency when compared to the conventional iterative division.

MISRA C is a collection of rules and recommendations for C programming language that is the de facto standard in industries where security plays the key role. The standard was developed by the MISRA (Motor Industry Software Reliability Association) consortium and includes a set of recommendations that allow the C language to be used to develop safe, reliable and portable software. MISRA is widely used in many industries with high reliability requirements, including aerospace, defense, automotive and medical.

We have developed static checkers to check code for compliance with MISRA C 2012 secure coding standard. The developed checkers are based on the LLVM/clang compiler infrastructure. This paper describes the strategies underlying the design and implementation of checkers. Using MISRA C 2012 example suite, the proposed checkers determine compliance or violation of the recommendations with high accuracy. The checkers also show greater coverage and better performance than Cppcheck, a popular open-source static analyzer.

This paper addresses the problem of named entities recognition from source code reviews. The paper provides a comparative analysis of existing approaches and proposes its own methods to improve the quality of problem solving. Proposed and implemented improvements include: methods to deal with data imbalances, improved tokenization of input data, the use of large arrays of unlabeled data, and the use of additional binary classifiers. To assess quality, a new set of 3,000 user code reviews was collected and manually labeled. It is shown that the proposed improvements can significantly increase the performance measured by quality metrics, calculated both at the token level (+22%) and at the entire entity level (+13%).

The study focuses on how modern GEC systems handle character-level errors. We discuss the ways these errors effect the performance of models and test how models of different architectures handle them. We conclude that specialized GEC systems do struggle against correcting non-existent words, and that a simple spellchecker considerably improve overall performance of a model. To evaluate it, we assess the models over several datasets. In addition to CoNLL-2014 validation dataset, we contribute a synthetic dataset with higher density of character-level errors and conclude that, provided that models generally show very high scores, validation datasets with higher density of tricky errors are a useful tool to compare models. Lastly, we notice cases of incorrect treatment of non-existent words on experts' annotation and contribute a cleared version of this dataset. In contrast to specialized GEC systems, LLaMA model used for GEC task handles character-level errors well. We suggest that this better performance is explained by the fact that Alpaca is not extensively trained on annotated texts with errors, but gets as input grammatically and orthographically correct texts.

Heavy oil fields are a promising energy source in the future due to the depletion of natural sources of light oil. However, extraction, transportation and refining of heavy oil is significantly more complicated than light oil - difficulties arise at almost all technological stages. One of such stages is laboratory analytics of heavy oil and selection of the most optimal catalyst for extraction of required fractions from crude oil sample. Different catalysts are actively used in petrochemical laboratories, but special attention is paid to those of them, the basis of which is metal. In this study, catalysts based on six different metals namely zinc, nickel, copper, manganese, lead and sodium were analyzed. In order to analyze the yield ratios of the required components from the crude heavy oil composition, it is necessary to test different types of catalysts sequentially on a base sample. The yield of different hydrocarbons on a small volume of oil can be reliably estimated by chromatographic study, which takes about 68 minutes for both the base oil sample and the different catalysts. Since testing 6 different catalysts would require almost 7 hours of chromatographic analysis, a rational solution would be to apply data mining techniques to this task. A multimodal transformer model was proposed to solve this problem. It takes as input two modalities: a chromatogram of a sample of pure crude oil presented as graphical data and accompanying tabular data, which are also generated by the chromatograph and consist of text and numbers. At the output, the model produces predictive tabular data that formalize the redistributed group composition of the oil and describe both the names of the newly produced hydrocarbons and their two qualitative characteristics: time and yield area. Obtaining the prediction makes it possible to significantly reduce the time, hardware and human resources required to select the right type of catalyst in petrochemical laboratories. In the process of the study, it was found that training of the intellectual model on the data of one field allows to perform further similar forecast with acceptable accuracy for the data of another heavy oil field. The magnitude of the prediction error of the intelligent model satisfies the requirements set by the petrochemical laboratory for practical application of the multimodal transformer.

We consider an actual approach to develop a physically based neural network for solving model problems for the Kovazhny flow, for the geophysical Beltrami flow, and for the flow in a section of the river by the shallow water theory. Physics-informed neural networks (PINN) allow to significantly reduce the computation time compared to conventional computations. There is a different analytical solution for each model flow. The architecture of the DeepXDE software library, its composition by modules, and fragments of program code in the Python programming language are discussed.  The PINN model is tested on a test sample. The prediction is evaluated using the MSE metric. The fully connected neural network can contain 4, 7, 10 hidden layers with the number of neurons 50, 50, 100 respectively.  The influence of hyperparameters of the neural network on the magnitude of the prediction error is discussed. The calculations performed on a server with Nvidia GeForce RTX 3070 card can significantly reduce the training time for PINN.

Studying the icing of ships is an urgent task. The paper considers the problem of modeling the flow of a model vessel with a gas-droplet flow and the occurrence of the icing process. Initially, the simulation was performed using the interDyMFoam solver, taking into account the assignment of the Stokes wave of the first kind to determine the position of the droplets. Further modeling was carried out using the iceFoam solver, which is based on the Euler-Lagrangian method for describing the gas-droplet flow. The considered model of a fishing vessel had a scale of 1:10. The position of the droplets was set at the entrance to the calculated rectangular domain. The estimated grid had from 1.5 to 10 million. cells. With the help of calculations, the trajectories of droplet movement around the hull of the vessel, the distribution of the air velocity field, the position of the water film and the thickness of ice on the deck surface were obtained. The mass of the overgrown ice was estimated. The simulation was performed on the computing cluster of the ISP RAS. One typical calculation was run on 48-96 computing cores and lasted no more than three days.

We study the generation of dust aerosol in the wind-driven cascading motion of charged particles over an irregular surface. The particles move under the influence of air flow over two elements of ripple type on an aeolian surface. Behind the obstacles the flow of saltation particles becomes non-uniform, the character of motion is noted by quasi-periodicity. The problem of including electrostatic effects into the hydrodynamic model, in which the mutual influence of particles and air medium is taken into account, was solved. A parametric model is proposed, which allows taking into account the chargeability of dust particles and the underlying surface in modeling wind transport. Computational experiments are carried out using the open source OpenFOAM package, the Eulerian-Lagrangian turbulent k-ω-model. Accordingly, the dynamics of charged particles is considered taking into account the electrification of the surface itself. From the results of computational experiments for different density characteristics of particles charged homonymously with the surface, the influence of the electric field on the frequency of change of the number of particles in the flow, on the scattering of values of velocities and the height of particle hops, as well as on the weakening of the effect of particles on the medium behind obstacles is estimated. When the influence of electrostatic effects is taken into account, an increase in the disturbing effect of particles flying after obstacles on the air medium is revealed (the distance from the obstacle increases, more local areas of disturbance appear). A decrease in the dispersion value is noted for the velocities of hopping particles. The height of particle jumps increases, which is confirmed by known experiments. The lower value of characteristic frequencies of change in the number of particles in the flow decreases. The non-uniformity of the particle flow determines changes in the intensity of dust aerosol generation.

As a rule, the main part of the computational costs in the numerical solution of problems in continuum mechanics consists in the solving of large sparse systems of linear algebraic equations. For this reason, efficient parallelization of this particular procedure can significantly speed up the simulation. To solve this problem, two main approaches can be used. The simplest approach consists in parallelizing of matrix-vector operations in a usual iterative solver. It requires several synchronization points and exchanges of coefficients at each iteration of the solver, which does not significantly speed up the simulation process as a whole. Therefore, domain decomposition methods are preferable. These methods involve dividing the computational domain into subdomains, constructing and solving separate problems in them, as well as some procedure to coordinate the solution between subdomains to ensure global convergence. Subdomains can overlap, as in the Schwartz method used in OpenFOAM, or they can be separated by interface sections, on which their own interface task is built, as in the Schur complement method. The latter method is used in this research to construct a parallel algorithm for viscous incompressible flow simulation by using the immersed boundary method LS-STAG with cut-cells and level-set functions. The resulting matrix of the interface system has a block tridiagonal structure. To speed up prototyping, OpenMP parallel programming technology is used in the software implementation of the developed algorithm, so computational experiments are carried out only on systems with shared memory, in particular on individual nodes of the educational and experimental cluster of the Applied Mathematics Department, Bauman Moscow State Technical University. To verify and evaluate the effectiveness of the developed parallel algorithm, a well-studied test problem about simulation of two-dimensional flow around a stationary circular airfoil is considered. Computations on a sequence of meshes with different numbers of subdomains show that the parallel algorithm allows one to obtain the same numerical solution as the original algorithm of the LS-STAG method, and the computed values of the Strouhal number and drag coefficient are in good agreement with the experimental and computational data known in the literature. Experiments demonstrate that the developed algorithm with domain decomposition allows to accelerate simulation even in sequential mode by reducing the number of solver iterations, i.e. the domain decomposition method acts as an additional preconditioner. Due to this property, the acceleration is superlinear when simulating in parallel mode with developed algorithm. This effect persists up to a certain number of subdomains, which depends on the size of the problem.