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8th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2018

作者： Schlick, Rupert Felderer, Michael Majzik, Istvan Nardone, Roberto Raschke, Alexander Snook, Colin Vittorini, Valeria Center for Digital Safety and Security AIT Austrian Institute of Technology GmbH Vienna Austria Department of Computer Science University of Innsbruck Innsbruck Austria Department of Software Engineering Blekinge Institute of Technology Karlskrona Sweden Department of Measurement and Information Systems Budapest University of Technology and Economics Budapest Hungary University of Naples Federico II Naples Italy Institute of Software Engineering and Programming Languages Ulm University Ulm Germany Electronics and Computer Science University of Southampton Southampton United Kingdom

ISBN: (纸本)9783030034269

Formal methods (in a broad sense) have been around almost since the beginning of computer science. Nonetheless, there is a perception in the formal methods community that take-up by industry is low considering the potential benefits. We take a look at possible reasons and give candidate explanations for this effect. To address the issue, we propose a repository of industry-relevant example problems with an accompanying open data storage for experiment results in order to document, disseminate and compare exemplary solutions from formal model based methods. This would allow potential users from industry to better understand the available solutions and to more easily select and adopt a formal method that fits their needs. At the same time, it would foster the adoption of open data and good scientific practice in this research field. © Springer Nature Switzerland AG 2018.

关键词： Formal methods

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Method of Detection of Intrusions Based on Stacking Meta-Algorithm

Method of Detection of Intrusions Based on Stacking Meta-Alg...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Vladislav Zozulia Nataliia Khatsko Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Department Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

An analysis of modern computer network intrusion detection systems was carried out. The application of machine and deep learning methods for classification problems has been investigated. The UNSW-NB15 dataset, developed at the Australian Cyber Security Center's (ACCS) Cyber Range Laboratory, contains data on normal network operations and synthetic intrusions. Data pre-processing was performed, including class balancing using the SMOTEENN method and selection of informative features using the Recursive Feature Elimination method. The possibility of using the stacking meta-algorithm to detect intrusions into computer networks has been investigated. A new algorithm for generating packets of raw data is proposed, which generates two sets of training data: one for training basic models, the other for a meta-model. A study of the effectiveness of using Random Forest, ANN, K Nearest Neighbor methods and Support Vector Machine and Random Forest as a decision-making meta-model was conducted. The use of the stacking meta-algorithm with the proposed algorithm for forming packets of output data, as well as basic models and a meta-model, led to a significant improvement in the quality of the model. It was found that, on average, recall and f1 score increased by 55.6% and 37.4%, respectively, compared to raw data and other models.

关键词： Training Support vector machines Computational modeling Stacking Training data Intrusion detection Predictive models Nearest neighbor methods Data models Random forests

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Methods for Improving the Quality of Classification on Imbalanced Data

Methods for Improving the Quality of Classification on Imbal...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Zozulia Vladislav Nataliia Khatsko Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Department of Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

The subject of the study is methods of balancing raw data. The purpose of the article is to improve the quality of intrusion detection in computer networks by using class balancing methods. Task: to investigate methods of balancing classes and to develop a classification method on imbalanced data to increase the level of network security. The methods used are: methods of artificial intelligence, machine learning. The following results were obtained: Class balancing methods based on Undersampling, Oversampling and their combinations were studied. The following methods were chosen for further research: SMOTEENN, SVMSMOTE, BorderlineSMOTE, ADASYN, SMOTE, KMeansSMOTE. The UNSW-NB 15 set was used as the source data, which contains information about the normal functioning of the network and during intrusions. A decision tree based on the CART (Classification And Regression Tree) algorithm was used as the basic classifier. According to the research results, it was found that the use of the SMOTEENN method provides an opportunity to improve the quality of detection of intrusions in the functioning of the network. Conclusions. The scientific novelty of the obtained results lies in the complex use of data balancing methods and the method of data classification based on decision trees to detect intrusions into computer networks, which made it possible to reduce the number of Type II errors.

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Using Natural Version Redundancy of FPGA Projects in Area of Critical Applications

Using Natural Version Redundancy of FPGA Projects in Area of...

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Oleksandr Drozd Vitaliy Romankevich Mykola Kuznietsov Myroslav Drozd Oleksandr Martynyuk Department of Computer Intelligent Systems and Networks Odessa National Polytechnic University Odessa Ukraine System programming and specialized computer systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine Department of Information Systems Odessa National Polytechnic University Odessa Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

The paper focuses on the role of version redundancy, which increases with the expansion of critical applications and the tightening of their functional safety requirements. International standards governing these requirements have already fixed the importance of version redundancy to counter common cause failures in safety-related systems. The problem of hidden faults inherent in these systems is equally acute, undermining confidence in the fault tolerance of circuit solutions important for functional safety. We suggest that this problem be seen as a growth problem where the system rises to the level of diversification in modes of operation by dividing them into normal and emergency and checkability circuits, but components continue to be stamped at a lower level of replication. Then the solution to the problem is to raise the components to the level of the system by developing their version redundancy. We demonstrate this development for FPGA components with LUT-oriented architecture and offer a method to improve the FPGA-ready project by natural version redundancy of its program code. The method generates a set of program code versions and selects versions that improve the checkability of circuits with respect to constant faults and the trustworthiness of results, respectively, in normal and emergency mode to reduce a set of hidden faults. The method is illustrated by an iterative array multiplier implemented in an FPGA project. Versions are generated, evaluated, and selected using the program developed for this.

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Word-Based Turkish Lip Reading System with Two Stream 3dcnn and Bilstm

SSRN

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SSRN 2023年

作者： Erbey, Ali Barışçı, Necaattin Department of Computer Programming Distance Education Vocational School Usak University Usak64200 Turkey Department of Information Systems Informatics Institute Gazi University Ankara Turkey Department of Computer Engineering Faculty of Technology Gazi University Ankara06500 Turkey

Lip reading is a technique that aims to understand spoken words by analyzing people's lip movements. Deep learning algorithms are used as a powerful tool for detecting and recognizing lip movements more accurately. In this study, we present a lip-reading architecture for the Turkish language. The architecture is trained to recognize Turkish words using 3DCNN (3D Convolutional Neural Network) architecture and two-stream deep learning methods. The model was trained on video data representing lip movements and learned to classify words accurately. The Turkish lip reading system has been trained and tested on a large Turkish lip reading dataset. In the experiments, an accuracy of 87.12% was achieved with the proposed model, indicating successful results in the Turkish language. The proposed model demonstrates high accuracy rates in recognizing Turkish words, showcasing its effectiveness. This paper introduces a novel architecture, a lip-reading system that employs deep learning techniques, providing a robust tool for successful Turkish lipreading applications. © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Advanced computer-Aided Optimization of Quartz Resonator-Based Sensors

Advanced Computer-Aided Optimization of Quartz Resonator-Bas...

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International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Volodymyr Savchenko Oksana Mnushka Oleg Sokulskyi Computer Engineering and Programming Department National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine Information Systems and Technologies Department National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine

ISBN: (数字)9798350378627

ISBN: (纸本)9798350378634

In this study, we present an improved approach to optimizing the parameters of sensor sensing elements using quartz resonators with an interelectrode gap. We combine graphical and analytical methods to solve the multi-criteria optimization problem. The work focuses on the modes of operation of a quartz resonator equipped with an interelectrode gap in sensors with a frequency output, determining a set of optimal parameters and representing them as surfaces in a particular optimization parameter space. The presented results reveal specific areas on the surface of the objective function where optimization of design and technological parameters is possible, taking into account technological influences and features of the sensor design, including the initial value of the interelectrode gap. By using an improved mathematical model for the oscillations of a quartz resonator with an electrode gap, this study achieves results with an accuracy of ($8 . . .11$)% higher than previous studies, demonstrating the effectiveness of the proposed method in improving the design and functionality of piezoelectric sensors for advanced applications.

关键词： Micromechanical devices Electrodes Accuracy Resonant frequency Linear programming Mathematical models Sensors

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Impact of fluctuation interferences to the responders performance of secondary surveillance radar system

Impact of fluctuation interferences to the responders perfor...

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International Conference on Radio Electronics & Info Communications (UkrMiCo)

作者： I.V. Svyd A.E. Goriushkina G.E. Zavolodko O.S. Maltsev Dept. Radiotechnologies Information and Communication Systems Kharkiv National University of Radio Electronics KNURE Kharkiv Ukraine Department of Computer science and Programming National Technical University «KhPI» NTU «KhPI» Kharkiv Ukraine Department of Information Systems National Technical University «KhPI» NTU «KhPI» Kharkiv Ukraine

ISBN: (数字)9781538652640

ISBN: (纸本)9781538652657

The principle of network construction and the principle of request signals service of Secondary surveillance radar systems predetermined the work of the respondents of the considered systems in conditions of intra-system and intentional correlated and uncorrelated interferences. The article estimates the impact of masking fluctuation interferences on the quality of the request signals detection. It is shown that the choice of time-interval codes as the request signals predetermined the low noise immunity of the considered systems when a channel is exposed by the fluctuation interference.

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Algorithmic Support for Building a Distributed IoT System in a Cloud Service

Algorithmic Support for Building a Distributed IoT System in...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Mykola Zamkovyi Svitlana Gavrylenko Kyrylo Khatsko Nataliia Khatsko dept. Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

The Internet of Things (IoT) today already connects billions of different IoT devices with the Internet. With the advent of new services and services, new challenges arise: how to make a cloud service publicly available, and reliable, how and where to store data. The article considers an example of the implementation of an IoT application with cloud components, considers the implementation of connecting IoT components to a cloud provider, and presents the IoT architecture. The focus is on the architecture and implementation of data exchange protocols, the implementation of protocols? for data collection and management of remote system components Given the large amount of data transmitted by IoT devices to the cloud, data compression and interaction with cloud services is a very relevant topic. Therefore, the article also offers recommendations for managing the traffic of IoT devices. The purpose of this article is to provide a description and algorithm for connecting IoT devices to the cloud, to bring together disparate information, and make it open and understandable to beginners and academic researchers.

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Creating a Dynamic Online Learning Environment with AI Integration

Creating a Dynamic Online Learning Environment with AI Integ...

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International computer Sciences and information Technologies (CSIT)

作者： Oleksandra Bulgakova Zarina Viniarska Viacheslav Zosimov P.M Platonov Educational and Scientific Institute of Computer Engineering Automation Robotics and Computer Programming Odesa National University of Technology Odesa Ukraine Department of Applied information systems Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

Educational, online learning has become a common practice due to rapid digitalization and recent global events. This study focuses on developing a comprehensive online learning platform that addresses users' needs by integrating advanced AI capabilities for personalized support and adaptive learning. The platform supports user registration and authentication, course and lesson management, and offers interactive features like AI-driven chat support. In this study, we show the importance of creating user-friendly online learning platforms with the implementation of modern AI trends. The development and testing of this platform is ongoing to determine the adaptation of the system to different learning styles.

关键词： Adaptive learning Electronic learning Authentication Passwords Market research Real-time systems Artificial intelligence information technology Standards Testing

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Social Engineering Attacks Detection Approach

Social Engineering Attacks Detection Approach

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Sergii Lysenko Volodymyr Vorobiov Oleksandr Bokhonko Piotr Gaj Oleg Savenko Jacek Wołoszyn Department of Computer Engineering and Information Systems Khmelnitsky National University Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Department of Computer Engineering and System Programming Khmelnitsky National University Khmelnitsky Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy.

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