Revnivykh A.V., Velizhanin A.S. —
Methods for automated formation of a disassembled listing structure
// Cybernetics and programming.
– 2019. – ¹ 2.
– P. 1 - 16.
DOI: 10.25136/2306-4196.2019.2.28272 URL: https://en. nbpublish.com/library_read_article.php?id=28272
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The subject of the research is the method of splitting a disassembled code into logical blocks in automatic mode, searching for software vulnerabilities without using source code (using a binary file or its equivalent, obtained by reverse engineering).The object of the research is the existing code analyzers and features of their functionality.The aim of the study is to consider the possibility of splitting a disassembled code into logical blocks in automatic mode and some of the possible difficulties associated with this.Formulation of the problem. The complexity of analyzing large software products at the level of machine code necessitates the automation of this process. The research methodology is based on a combination of theoretical and empirical approaches using the methods of static and dynamic analysis, comparison, generalization, algorithmization, modeling, synthesis. Key findings. Splitting the code into blocks by sequential in line-by-line analysis of machine code in some cases can lead to misinterpretation. In addition, the analysis of the code according to the conclusions of the functions also does not guarantee the correctness of the determination of the boundaries of the functions. However, in general, the matrix method can be applied to analyze the dependencies of functions on the blocks of code thus selected.The scientific novelty is connected with the determination of promising vectors for the study of software code for vulnerability, the rationale for the approach (building the transition matrix from integer values), which may be the initial stage of preparation for the automated analysis of the disassembled code.
Matrix method, Adjacency matrix, IDA Pro utility, FASM compiler, Disassembling, Code analyses, Vulnerabilities, Information security, Code blocks, Matrix building algorithm
Kozachok A. V., Kochetkov E. V. Obosnovanie vozmozhnosti primeneniya verifikatsii programm dlya obnaruzheniya vredonosnogo koda. // Voprosy kiberbezopasnosti. — 2016. — Byp. 3(16). — S. 25–32. ISSN 2311-3456.
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Fedotov A. N. Metod otsenki ekspluatiruemosti programmnykh defektov // Trudy instituta sistemnogo programmirovaniya RAN. — 2016. — T. 28. — ¹ 4. — S. 137–148. ISSN 2079-8156. DOI: 10.15514/ISPRAS-2016-28(4)-8.
Nepomnyashchikh A. V., Kulikov G. V., Sosnin Yu. V., Nashchekin P. A. Metody otsenivaniya zashchishchennosti informatsii v avtomatizirovannykh sistemakh ot nesanktsio
Mathematical models and computer simulation experiment
Efimov A.I., Balily N.A. —
Methods of teaching control systems for unmanned aerial vehicles by immersing them in virtual reality
// Cybernetics and programming.
– 2019. – ¹ 2.
– P. 17 - 22.
DOI: 10.25136/2306-4196.2019.2.29236 URL: https://en. nbpublish.com/library_read_article.php?id=29236
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The subject of study is the implementation of control systems for unmanned aerial vehicles. As their solution, a method of teaching and testing of these systems by immersing the entire system and its individual components into a virtual reality as close as possible to real conditions is proposed. The advantages and difficulties of implementation in relation to each of the system modules involved are considered. For each of the difficulties the authors propose solutions. The most successful scopes of application are revealed, and also possibility of application of the given method to land and surface vehicles is allocated. In the framework of this work, the existing aircraft control systems and the use of virtual reality within the framework of training their individual parts are investigated and the option of extending the use of such methods to the entire control system with an analysis of the advantages and disadvantages of this approach is proposed. The novelty of this article lies in the training of control systems for unmanned aerial vehicles by immersing it in virtual reality. The completeness and flexibility of such a training system is able, on the one hand, to adapt to any equipment configuration, on the other hand, to provide the highest quality training. The most important aspect is ensuring that you can use a larger proportion of the learning algorithms than is possible in other cases. In addition, this approach to the crane is useful in the framework of video navigation in connection with the possibility of better implementation of computer vision. The article shows the relevance of the research and the effectiveness of this method in the framework of aircraft control systems and proposed its application to other vehicles.
learning algorithms, computer vision, navigation, control system, virtual reality, unmanned aerial vehicle (UAV), neural networks, deep learning, drone, videonavigation
K. E. Shilov Razrabotka sistemy avtomaticheskogo upravleniya bespilotnym letatel'nym apparatom mul'tirotornogo tipa TRUDY MFTI, Moskva, 2014, Tom 6, ¹ 4, c. 139–152
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Nati Amsterdam Testing, Testing: How VR Can Spin the Odometer Forward