Volume 21, Nº 2 (2022)

Ano: 2022
Artigos: 8
URL: https://journal-vniispk.ru/2713-3192/issue/view/17152

Edição completa

Information security

Model Checking for Real-Time Attack Detection in Water Distribution Systems

Mercaldo F., Martinelli F., Santone A.

Resumo

Water distribution systems represents critical infrastructures. These architectures are really critical and an irregular behaviour can be reflected in human safety. As a matter of fact, an attacker obtaining the control of such of an architecture is able to perpetrate a plethora of damages, both to the infrastructure but also to people. In this paper, we propose an approach to identify irregular behaviours focused on water distribution systems. The designed approach considers formal verification environment. The logs retrieved from water distribution systems are parsed into a formal model and, by exploiting timed temporal logic, we characterize the behaviour of a water distribution system while an attack is happening. The evaluation, referred to a water distribution system, confirmed the effectiveness of the designed approach in the identification of three different irregular behaviours.

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Informatics and Automation. 2022;21(2):219-242

219-242

(Eng)

(JATS XML)

Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors

Bui P., Le M., Hoang B., Ngoc N., Pham H.

Resumo

Nowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-core processors to ensure information security and increase the performance of embedded software have not received much attention. The paper proposes and develops the embedded software performance improvement method on multi-core processors based on data partitioning and asynchronous processing. Data are used globally to be retrieved by any threads. The data are divided into different partitions, and the program is also installed according to the multi-threaded model. Each thread handles a partition of the divided data. The size of each data portion is proportional to the processing speed and the cache size of the core in the multi-core processor. Threads run in parallel and do not need synchronization, but it is necessary to share a general global variable to check the executing status of the system. Our research on embedded software is based on data security, so we have tested and assessed the method with several block ciphers like AES, DES, etc., on Raspberry PI3. The average performance improvement rate achieved was 59.09%.

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Informatics and Automation. 2022;21(2):243-274

243-274

(Eng)

(JATS XML)

Comprehensive Defense System against Vulnerabilities Based on Return-Oriented Programming

Lubkin I., Zolotarev V.

Resumo

It is difficult or impossible to develop software without included errors. Errors can lead to an abnormal order of machine code execution during data transmission to a program. Program splitting into routines causes possible attacks by using return instructions from these routines. Most of existing security tools need to apply program source codes to protect against such attacks. The proposed defensive method is intended to a comprehensive solution to the problem. Firstly, it makes it difficult for an attacker to gain control over program execution, and secondly, the number of program routines, which can be used during the attack, decreases. Specific security code insertion is used at the beginning and end of the routines to make it complicated to gain control over the program execution. The return address is kept secure during a call of the protected routine, and the protected routine is restored after its execution if it was damaged by the attacker. To reduce the number of suitable routines for attacks, it was suggested to use synonymous substitutions of instructions that contain dangerous values. It should be mentioned that proposed defensive measures do not affect the original application`s algorithm. To confirm the effectiveness of the described defensive method, software implementation and its testing were accomplished. Acknowledging controls were conducted using synthetic tests, performance tests and real programs. Results of testing have demonstrated the reliability of the proposed measures. It ensures the elimination of program routines suitable for attacks and ensures the impossibility of using standard return instructions for conducting attacks. Performance tests have shown a 14 % drop in the operating speed, which approximately matches the level of the nearest analogues. The application of the proposed solution declines the number of possible attack scenarios, and its applicability level is higher in comparison with analogues.

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Informatics and Automation. 2022;21(2):275-310

275-310

(Rus)

(JATS XML)

Mathematical modeling and applied mathematics

Identification of Deterioration caused by AHF, MADS or CE by RR and QT Data Classification

Abramov M., Tsukanova E., Tulupyev A., Korepanova A., Aleksanin S.

Resumo

A sharp deterioration of the patient’s condition against the backdrop of the development of life-threatening arrhythmias with symptoms of acute heart failure (AHF), multiple organ dysfunction syndrome (MODS) or cerebral edema (CE) can lead to the death of the patient. Since the known methods of automated diagnostics currently cannot accurately and promptly determine that the patient is in a life-threatening condition leading to the fatal outcome caused by AHF, MODS or CE, there is a need to develop appropriate methods. One of the ways to identify predictors of such a state is to apply machine learning methods to the collected datasets. In this article, we consider using data analysis methods to test the hypothesis that there is a predictor of death risk assessment, which can be derived from the previously obtained values of the ECG intervals, which gives a statistically significant difference for the ECG of the two groups of patients: those who suffered deterioration leading to the fatal outcome caused be MODS, AHF or CE, and those with favorable outcome. A method for unifying ECG data was proposed, which allow, based on the sequence of RR and QT intervals, to the construct of a number that is a characteristic of the patient's heart condition. Based on this characteristic, the patients are classified into groups: the main (patients with fatal outcome) and control (patients with favorable outcome). The resulting classification method lays the potential for the development of methods for identifying the patient's health condition, which will automate the detection of its deterioration. The novelty of the result lies in the confirmation of the hypothesis stated above, as well as the proposed classification criteria that allow solving the urgent problem of an automatic detection of the deterioration of the patient's condition.

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Informatics and Automation. 2022;21(2):311-338

311-338

(Eng)

(JATS XML)

Modeling the Dynamics of Collective Behavior in a Reflexive Game with an Arbitrary Number of Leaders

Algazin G., Algazina D.

Resumo

An oligopoly with an arbitrary number of Stackelberg leaders under incomplete, asymmetrical agents' awareness and inadequacy of their predictions of competitors' actions is considered. Models of individual decision-making processes by agents are studied. The reflexive games theory and collective behavior theory are the theoretical basis for construction and analytical study process models. They complement each other in that reflexive games allow using the collective behavior procedures and the results of agents' reflections, leading to a Nash equilibrium. The dynamic decision-making process considered repeated static games on a range of agents' feasible responses to the expected actions of the environment, considering current economic restrictions and competitiveness in each game. Each reflexive agent in each game calculates its current goal position and changes its state, taking steps towards the current position of the goal to obtain positive profit or minimize losses. Sufficient conditions for the convergence of processes in discrete time for the case of linear costs of agents and linear demand is the main result of this work. New analytical expressions for the agents' current steps' ranges guarantee the convergence of the collective behavior models to static Nash equilibrium is obtained. That allows each agent to maximize their profit, assuming common knowledge among the agents. The processes when the agent chooses their best response are also analyzed. The latter may not give converging trajectories. The case of the duopoly in comparison with modern results is discussed in detail. Necessary mathematical lemmas, statements, and their proofs are presented.

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Informatics and Automation. 2022;21(2):339-375

339-375

(Rus)

(JATS XML)

Artificial intelligence, knowledge and data engineering

Fuzzy Logic Approaches in the Task of Object Edge Detection

Bobyr M., Arkhipov A., Gorbachev S., Cao J., Bhattacharyya S.

Resumo

The task of reducing the computational complexity of contour detection in images is considered in the article. The solution to the task is achieved by modifying the Canny detector and reducing the number of passes through the original image. In the first case, two passes are excluded when determining the adjacency of the central pixel with eight adjacent ones in a frame of size 3х3. In the second case, three passes are excluded, two as in the first case and the third one necessary to determine the angle of gradient direction. This passage is provided by a combination of fuzzy rules. The goal of the work is to increase the performance of computational operations in the process of detecting the edges of objects by reducing the number of passes through the original image. The process of edge detection is carried out by some computational operations of the Canny detector with the replacement of the most complex procedures. In the proposed methods, fuzzification of eight input variables is carried out after determining the gradient and the angle of its direction. The input variables are the gradient difference between the central and adjacent cells in a frame of size 3х3. Then a base of fuzzy rules is built. In the first method, four fuzzy rules and one pass are excluded depending on the angle of gradient direction. In the second method, sixteen fuzzy rules themselves set the angle of the gradient direction, while eliminating two passes along the image. The gradient difference between the central cell and adjacent cells makes it possible to take into account the shape of the gradient distribution. Then, based on the center of gravity method, the resulting variable is defuzzified. Further use of fuzzy a-cut makes it possible to binarize the resulting image with the selection of object edges on it. The presented experimental results showed that the noise level depends on the value of the a-cut and the parameters of the labels of the trapezoidal membership functions. The software was developed to evaluate fuzzy edge detection methods. The limitation of the two methods is the use of piecewise-linear membership functions. Experimental studies of the performance of the proposed edge detection approaches have shown that the time of the first fuzzy method is 18% faster compared to the Canny detector and 2% faster than the second fuzzy method. However, during the visual assessment, it was found that the second fuzzy method better determines the edges of objects.

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Informatics and Automation. 2022;21(2):376-404

376-404

(Rus)

(JATS XML)

Crop Identification Using Radar Images

Dubrovin K., Stepanov A., Verkhoturov A., Aseeva T.

Resumo

One of the most important tasks in practical agricultural activity is the identification of agricultural crops, both those growing in individual fields at the moment and those that grew in these fields earlier. To reduce the complexity of the identification process in recent years, data from remote sensing of the Earth (remote sensing), including the values of vegetation indices calculated during the growing season, have been used. At the same time, processing optical satellite images and obtaining reliable index values is often difficult, which is due to cloud cover during the shooting. To solve this problem, the article suggests using the seasonal course curve of the radar vegetation index with double polarization (DpRVI) as the main indicator characterizing agricultural crops. In the period 2017-2020, 48 radar images of the Khabarovsk Municipal District of the Khabarovsk Territory from the Sentinel-1 satellite were received and processed to identify crops in the experimental fields of the Far Eastern Research Institute of Agriculture (FEARI) (resolution 22 m, shooting interval - 12 days). Soybeans and oats were the main identified crops. Pixels of fields not occupied by these crops (forage grasses, abandoned fields) were also added. The series of values of DpRVI were obtained both for individual pixels and fields, and approximated series for three classes. The approximation was carried out using the Gaussian function, the double logistic function, the square and cubic polynomials. It is established that the optimal approximation algorithm is the use of a double logistic function (the average error was 4.6%). On average, the approximation error of the vegetation index for soybeans did not exceed 5%, for perennial grasses – 8.5%, and for oats - 11%. For experimental fields with a total area of 303 hectares with a known crop rotation, the classification was carried out by the weighted method of k nearest neighbors (the training sample was formed according to the data of 2017-2019, the test sample -2020). As a result, 90% of the fields were correctly identified, and the overall pixel classification accuracy was 73%, which made it possible to identify the discrepancy between the actual boundaries of the fields declared to identify abandoned and swampy areas. Thus, it is established that the DpRVI index can be used to identify agricultural crops in the south of the Far East and serve as the basis for the automatic classification of arable land.

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Informatics and Automation. 2022;21(2):405-426

405-426

(Rus)

(JATS XML)

Analysis of Multi-Temporal Multispectral Aerial Photography Data to Detect the Boundaries of Historical Anthropogenic Impact

Shaura A., Zlobina A., Zhurbin I., Bazhenova A.

Resumo

The article presents the application of a statistical analysis algorithm for multi-temporal multispectral aerial photography data to identify areas of historical anthropogenic impact on the natural environment. The investigated site is located on the outskirts of the urban-type village of Znamenka (Znamensky District, Tambov Region) in a forest-steppe zone with typical chernozem soils, where arable lands were located in the second half of the 19th - early 20th centuries. Grown vegetation as a result of secondary succession in abandoned areas can be a sign for identifying traces of historical anthropogenic impact. Distinctive signs of such vegetation from the surrounding natural environment are its type, age and growth density. Thus, the problem of detecting the boundaries of anthropogenic impact on multispectral images is reduced to the problem of vegetation classification. The initial data were the results of multi-temporal multispectral imaging in green (Green), red (Red), edge of red (RedEdge) and near-infrared (NIR) spectral ranges. The first stage of the algorithm is the calculation of the Haralick texture features on multispectral images, the second stage – reduction in the number of features by the principal component analysis, the third stage – the segmentation of images based on the obtained features by the k-means method. The effectiveness of the proposed algorithm is shown by comparing the segmentation results with the reference data of historical cartographic materials. The study of multi-temporal multispectral images makes it possible to more fully characterize and take into account the dynamics of phytomass growth in different periods of the growing season. Therefore, the obtained segmentation result reflects not only the configuration of areas of an anthropogenic transformed natural environment, but also the features of overgrowth of abandoned arable land.

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Informatics and Automation. 2022;21(2):427-453

427-453

(Rus)

(JATS XML)

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