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The way to detection of software emergent properties

The way to detection of software emergent properties

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IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Oksana Pomorova Tetiana Hovorushchenko Department of System programming Khmelnitsky National University Khmelnitsky Ukraine

The paper deals with the problem of detection of imperfections of software quality evaluation. Existing currently models and methods of the software quality evaluation weakly take into account the systemic aspect of modern software, including they pay insufficient attention to emergent properties of software. Analysis of the known approaches of software emergent properties detection showed that nowadays these approaches are theoretical and only explain the nature of emergent properties. But these appoaches don't provide the prediction of the emergence and evaluation of the influence of emergent properties in the software system. So the methodologies of software quality evaluation require the significant development in part of detection, evaluation and prediction of emergent properties, and also in the part of full consideration of the subject domain information at the different stages of the software life cycle.

关键词： Software quality Accidents Software systems Complexity theory Complex systems Software reliability

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Research of artificial neural network's component of software quality evaluation and prediction method

Research of artificial neural network's component of softwar...

引用

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Oksana Pomorova Tetyana Hovorushchenko System programming Department Khmelnitsky National University Khmelnitskiy Ukraine

This paper represents the artificial neural network's method of design results evaluation and software quality characteristics prediction (NMEP) and the analysis of results of realized artificial neural network (A... 详细信息

关键词： Measurement Artificial neural networks Training Complexity theory Software quality Vectors

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Assessment of the source code static analysis effectiveness for security requirements implementation into software developing process

Assessment of the source code static analysis effectiveness ...

引用

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Oksana V. Pomorova Dmytro O. Ivanchyshyn System Programming Department Khmelnytskyi National University Khmelnitsky Ukraine

The article focuses on the problem of software security assurance. The place of source code security analysis in the software lifecycle was considered. Results of common tools for C and C++ source code static analysis... 详细信息

关键词： Software Security Software measurement Model checking Phase measurement

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DNS-based anti-evasion technique for botnets detection

DNS-based anti-evasion technique for botnets detection

引用

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Sergii Lysenko Oksana Pomorova Oleg Savenko Andrii Kryshchuk Kira Bobrovnikova Department of System Programming Khmelnitsky National University Khmelnitsky Ukraine

A new DNS-based anti-evasion technique for botnets detection is proposed. It is based on a cluster analysis of the features obtained from the payload of DNS-messages. The method uses a semi-supervised fuzzy c-means clustering. Usage of the developed method makes it possible to detect botnets that use the DNS-based evasion techniques with high efficiency.

关键词： Feature extraction Servers IP networks Entropy Payloads Buildings Internet

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Comparative Study for Classification Methods to Predict and Detect Epilepsy Seizure 5

Comparative Study for Classification Methods to Predict and ...

引用

5th IEEE Middle East and Africa Conference on Biomedical Engineering, MECBME 2020

作者： El Halabi, Nashaat Abi Zeid Daou, Roy Achkar, Roger Hayek, Ali Boercsoek, Josef American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany

ISBN: (纸本)9781728123585

Epilepsy is a medical problem that tackles lots of patients. It limits the life activity of such patients due to the seizures that occur anytime and anywhere. Thus, creating a monitoring system that could make their life easier and allow them to perform daily life activities as safe as possible has been studied. This paper is a continuity for a project where a system monitors epileptic patients using a set of wearable sensors connected to several processing units, the main sensors are Electroencephalogram (EEG) for the electrical activity of the brain, electrocardiogram (ECG) for the electrical activity of the heart, and accelerometers to monitor the posture of the patient, features extracted from EEG and ECG signals are used for prediction/detection of seizures. Thus, the objective of this paper is to present a comparative study in order to choose the appropriate classification method for seizure prediction and detection. Five classification methods were studied: Decision Trees, Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Ensemble Learning. For each of the classification methods, the accuracy, the specificity, the sensitivity, the precision, the false detection rate and the Fmeasure were studied and compared. The results for seizure prediction system show that the highest accuracy, specificity and F-Measure, and lowest false detection rate were achieved with Bagged Trees Ensemble Learning, the highest sensitivity and precision were achieved with Quadratic Support Vector Machine. However, for seizure detection system, the highest accuracy and F-Measure were achieved with Linear Support Vector, the highest sensitivity and specificity were achieved with Fine Gaussian Support Vector Machine, and the highest precision and lowest false detection rate were achieved with Subspace Discriminant Ensemble Learning. © 2020 IEEE.

关键词： Support vector machines

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Realization of the neural network model of prediction of the software project characteristics for evaluating the success of its implementation

Realization of the neural network model of prediction of the...

引用

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Tetiana Hovorushchenko Andriy Krasiy Department System Programming Khmelnitsky National University Khmelnitsky Ukraine

This paper proves the dependence of successful of software project implementation on the software requirements specification (SRS), the actuality and importance of the skill to evaluate the possible success of software project based on the specifications. The neural network model of prediction of the software project characteristics for evaluating the success of its implementation based on analysis of specifications is first time proposed and implemented in Matlab.

关键词： Software Artificial neural networks Neurons Training Biological neural networks Mathematical model Predictive models

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Software development for safety-related systems

Software development for safety-related systems

引用

ICONS International Conference on systems

作者： Josef Borcsok Sebastian Schaefer Department of Computer Architecture and System Programming University of Kassel Germany

Safety-related systems mostly comprise hardware and software solutions. Due to the increasing application of complex hardware and software systems, the software systems have to be considered regarding safety as well as hardware systems. The development of a safety-related software system is similar to the development of a safety-related hardware systems. But there are still no generally accepted methods for developing safety-critical software. One has to use the methods, which fit best to the actual requirements. However, the calculation of reliability and availability for safety-related software systems is far more complex.

关键词： programming Software safety Software systems Hardware Software testing Software design Application software Object oriented modeling Computer architecture Documentation

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Botnet detection technique for corporate area network

Botnet detection technique for corporate area network

引用

IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications

作者： Oleg Savenko Sergii Lysenko Andrii Kryshchuk Yuriy Klots Department of System Programming Khmelnitsky National University Khmelnitsky Ukraine

A new approach for the botnet detection based on multi-agent system is proposed. For increasing of the efficiency of botnet detection the multi-agent system was involved that allowed to make botnet detection via agents' communication within corporate network. A new technique with the usage of fuzzy and neural-fuzzy systems that makes the conclusion about botnet presence degree in computer systems is developed. The analysis of the botnets' actions demonstrations in the situation of the intentionally computer system reconnection is performed. It takes into account the botnet demonstrations in the several computer systems which are available in the network.

关键词： Computers Multi-agent systems Fuzzy logic Computational modeling Monitoring Software Malware

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Training Policy for Privacy-Preserving Logistic Regression in Federated Learning Environments 2

Training Policy for Privacy-Preserving Logistic Regression i...

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2nd IEEE International Conference on Federated Learning Technologies and Applications, FLTA 2024

作者： Cortés-Mendoza, Jorge M. Tchernykh, Andrei González-Vélez, Horacio Cloud Competency Centre National College of Ireland Dublin Ireland Computer Science Department CICESE Research Center Ensenada Mexico Institute for System Programming RAS Moscow Russia

ISBN: (纸本)9798350354812

Logistic Regression (LR) is a widely used statistical model for classification problems. However, its training and evaluation in a shared environment increase the possibility of information leaking. A federated LR reduces security issues by using only locally available data for training. In a Federated Learning (FL) environment, LR receives the coefficients of local models to create the federated LR model, which is then distributed to update the local models. The exchange process does not leak confidential information when LR coefficients are encrypted. Homomorphic Encryption (HE) allows the merging of local LR models with privacy preservation (HE-LR). This work presents a novel training policy to reduce the training time with only slightly decreased quality in an FL environment with HE. We analyze the accuracy and time of FL policies with HE-LR that progressively reduce the amount of training data and exchange the LR coefficients in a privacy-preserving manner. The results show that the proposed policy can speed up the training time between 12% and 69%, compared to the traditional FL approach, with an average decrease in accuracy of 1.79% and 1.95%. ©2024 IEEE.

关键词： Differential privacy

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Validation of a newly developed implementation of the PFEM-2 method using an open-source framework

Validation of a newly developed implementation of the PFEM-2...

引用

2021 Ivannikov Ispras Open Conference, ISPRAS 2021

作者： Popov, Andrey Marchevsky, Ilia Serbin, Georgy Bauman Moscow State Technical University Fundamental Sciences Department Moscow Russia Ivannikov Institute For System Programming Of The Ras Bauman Moscow State Technical University Moscow Russia

ISBN: (纸本)9781665423304

A description of a newly developed implementation of the Particle Finite Element Method, 2nd generation (PFEM-2) is given. Main steps of the FEM and particles' parts of the algorithm are outlined. The results of its validation for a benchmark computation of a laminar flow are presented. Comparison with results obtained in the OpenFOAM code is also given. © 2021 IEEE.

关键词： Finite element method

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