The considered method of program code protection with the use of obfuscation mechanisms allows to confuse the code during development and refactoring. This method protects against decompilation methods that can be applied both manually and automatically. The aim of the study is to develop a method of obfuscating software code to provide protection against decompilation. To achieve this goal, the following tasks are solved: analyzed algorithms of deobfuscation in various practical methods; a new method of obfuscating program code is proposed; submit obfuscated code. The main stages of the proposed approach to obfuscation of programs are formulated: lexical analysis; code destructuring; code obfuscation; obfuscation of variables; obfuscation of constants. Different strategies for the synthesis of obfuscated identifiers are defined: generation of names, consisting of admissible random (pseudo-random) symbols, length from the set interval (fixed length); generating names consisting of a certain number of repeated valid characters, in conditions where the plurality of characters is specified and the specified length of the lengths of the identifiers; mixed strategy with equal choice of strategies 1 and 2. Two optimization problems are formulated: the task of minimizing the number of operations when generating a given set of constants with a fixed set of directly defined constants; the task of minimizing the number of directly defined constants among the options with minimal complexity of formulas. The proposed approach can be used in programs that have a number of routines with the same interface. In this case, regardless of the complexity of implementation, the code of each subroutine can be converted into destructured code. After that, it is possible to calculate the total number of feasible operators, taking into account (operator) output for all routines.
An artificial neural system for data compression that sequentially processes linearly nonseparable classes is proposed. The main elements of this system include adjustable radial-basis functions (Epanechnikov’s kernels), an adaptive linear associator learned by a multistep optimal algorithm, and Hebb-Sanger neural network whose nodes are formed by Oja’s neurons. For tuning the modified Oja’s algorithm, additional filtering (in case of noisy data) and tracking (in case of nonstationary data) properties were introduced. The main feature of the proposed system is the ability to work in conditions of significant nonlinearity of the initial data that are sequentially fed to the system and have a non-stationary nature. The effectiveness of the developed approach was confirmed by the experimental results. The proposed kernel online neural system is designed to solve compression and visualization tasks when initial data form linearly nonseparable classes in general problem of Data Stream Mining and Dynamic Data Mining. The main benefit of the proposed approach is high speed and ability to process data whose characteristics are changed in time.
Поява в Україні операторських мереж з концепцією доступу IoT потребує розробки технічних та програмних засобів для управління відповідними пристроями та сервісами. Найбільша кількість кейсів спостерігається в обслуговуванні приватних виробничих мереж М2М, державних мереж з обмеженим або закритим доступом, приватних домашніх мереж, в тому числі, приватних комунальних господарств,. Розглянуто особливості побудови IoT мереж в цілому, визначено їх завдання та специфіку фізичної архітектури IoT рішень. Проведено аналіз процесів формування, перетворення та передачі фізичних сигналів в мережі IoT. Визначено, що підсистеми IoT стикуються ненадійним каналом зв'язку, тому потребують розробки механізмів гарантованої доставки інформації. Проведено аналіз інфраструктури рішень IoT, що використовуються в промисловості для автоматизації промислових сервісів. Розглянуто структурну схему розгортання інфраструктури LPWAN мережі. Наведено перелік конкурентних платформ, що можуть використовуватися для автоматизації промислових сервісів. Підняте питання кібербезпеки в мережах IoT. Проведено аналіз інцидентів несанкціонованих втручання в мережу, які призвели до тимчасової відмови сервісів та заподіяли значної шкоди кінцевим споживачам послуг. Розглянуто методи перешкоджання кібератакам в мережах IoT. Проведено аналіз використання рішень на основі стандарту NB-IoT та рішень на базі IoT для автоматизації промислових сервісів та з точки зору забезпечення безпеки в приватних мережах. Запропоновано методику вибору рішення з урахуванням вимог до бізнес-процесів кінцевих споживачів сервісів та технічних можливостей оператора. Розглянуто переваги приватних NB-IoT-мереж порівняно з LPWAN.
This article is about developing a security assessment system for smart homes that use Internet of Things technology. The Internet of Things (IoT) is a nascent paradigm focused on the relationship of things or devices to each other and users. Over time, most connections on the Internet of Things go from «people interact with things» to «things interact with things». This technology is expected to be an important milestone in the development of smart homes to bring convenience and efficiency to our lives and our homes. But the introduction of this IoT technology in our homes will be important for the safety of these technologies. Connecting all smart objects inside the house to the Internet and to each other leads to new security and privacy issues, such as the confidentiality, authenticity, and integrity of the data that is perceived and exchanged. These technologies are very vulnerable to various security attacks that make a smart home based on IoT unsafe to live in, so security risks need to be assessed to assess the situation of smart homes. For any technology to be successful and widely used, it must gain the trust of users, ensuring sufficient security and confidentiality. As in all sectors, maintaining security will be the most important challenge to overcome. As homes become more computerized and filled with devices, potential computer security attacks and their impact on residents need to be investigated. This paper uses a methodology that focuses mainly on information assets and examines containers (technical, physical and human) and conducts security risk assessments to highlight various security vulnerabilities in the smart home based on the Internet of Things, the consequences and proposing measures against identified problems. that meet most safety requirements. Finally, it offers recommendations for users.
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