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Application of Machine Learning Techniques for Software Anomaly Detection

Application of Machine Learning Techniques for Software Anom...

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International Conference on Applied Mathematics & computer Science (ICAMCS)

作者： Veska Gancheva Department of Programming and Computer Technologies Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

A rising variety of platforms and software programs have leveraged repository-stored datasets and remote access in recent years. As a result, datasets are more vulnerable to malicious attacks. As a result, network security has grown in importance as a research topic. The usage of intrusion detection systems is a well-known strategy for safeguarding computer networks. This paper proposes an anomaly detection method that blends rule-based and machine-learning-based methods. In order to construct the appropriate rules, a genetic algorithm is utilized. Principal component analysis is used to extract the relevant features aimed to improve the performance. The suggested method is validated experimentally using the KDD Cup 1999 dataset, which meets the requirement of using appropriate data. The proposed method is applied to detect and analyze four types of attacks in a well-known benchmark dataset: Neptune, Ipsweep, Pod, and Teardrop, utilizing Support Vector Machine, Decision Tree, and Naive Bayes algorithms. After testing the characteristics specified in the training phase, the data is classified into attack categories and normal behavior during the machine learning phase.

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Using Natural Language Processing for Quality Assurance Purposes in Higher Education

Using Natural Language Processing for Quality Assurance Purp...

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2021 International Conference on High Technology for Sustainable Development, HiTech 2021

作者： Ujkani, Berat Minkovska, Daniela Stoyanova, Lyudmila Technical University of Sofia Department of Programming and Computer Technologies Sofia Bulgaria

ISBN: (纸本)9781665448734

Nowadays, quality is the most important attribute that creates value. It is considered as the competitive advantage of private and public organizations by which they differentiate their products or services. Quality assurance in higher education is concerned more than ever before. This paper presents a system intended to facilitate some aspects of the quality assurance process in the universities by helping both the quality assurance officers as well as lecturers. The system accepts as an input the learning outcomes of syllabuses and program curricula and based on some specific rules performs consistency checks between them, assuring that program delivers to students what it actually promises. © 2021 IEEE.

关键词： Curricula

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Input Data Time Range Impact on Forecast Quality Using Automated Procedures 11

Input Data Time Range Impact on Forecast Quality Using Autom...

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11th International Scientific Conference on computer Science, COMSCI 2023

作者： Koparanov, Kiril Andreev Antonova, Elena Ventseslavova Nakov, Ognyan Nakov Minkovska, Daniela Veleva Georgiev, Krasin Krasimirov Stoyanova, Lyudmila Yordanova Technical University of Sofia Faculty of Computer Systems and Technologies Department of Programming and Computer Technologies 8 Kliment Ohridski blvd Sofia1000 Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Department of Computer Systems 8 Kliment Ohridski blvd Sofia1000 Bulgaria Technical University of Sofia Faculty of Transport Department of Air Transport 8 Kliment Ohridski blvd Sofia1000 Bulgaria

ISBN: (纸本)9798350325256

Easy access to time series forecasting provides a strong competitive advantage for any company or organization. As automated forecasting environments become more prevalent in the market, it is crucial to explore their capabilities and features to utilize them competently. This study demonstrates the influence of data coverage on prediction accuracy and validates the initial assumption. Based on the findings, recommendations have been presented to enhance the quality of predictive processes. © 2023 IEEE.

关键词： Forecasting

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An Approach to Investigating Plagiarism in Artificial Intelligence Content

An Approach to Investigating Plagiarism in Artificial Intell...

引用

computer Science (COMSCI), International Scientific Conference on

作者： Daniela Veleva Minkovska Elena Ventseslavova Antonova Kiril Andreev Koparanov Plamen Ognyanov Nakov Department of Programming and Computer Technologies Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria Department of Computer Systems Faculty of Computer Systems and Technologies Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350392166

ISBN: (纸本)9798350392173

A growing number of human-centric tasks like learning, planning, and creative writing require the integration of Artificial Intelligence (AI) in the current era of exponential advancements. Such systems collect and analyze data on their own making the best use of available resources and providing creative solutions for challenging issues. The impact of AI on productivity, data analysis, flexibility, and real-time decision- making in a variety of fields is examined in this paper. Focusing on academic settings, the paper considers ethical concerns surrounding AI-generated content. According to a survey, even though many students use ChatGPT for writing and research, worries about academic integrity and plagiarism still exist.

关键词： Surveys Productivity Ethics Plagiarism Writing Chatbots Real-time systems Trajectory Artificial intelligence Standards

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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A Zero-Watermarking Algorithm for Use in RGB and Monochrome Images

A Zero-Watermarking Algorithm for Use in RGB and Monochrome ...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Vadym Poddubnyi Roman Gvozdov Oleksandr Sievierinov Vladyslav Sukhoteplyi Serhii Bulba Dmytro Lysytsia Department of of information technology security Kharkiv National University of Radio Electronic Kharkiv Ukraine Department of Computer Engineering and Programming Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The article proposes a method of zero-watermarking for colored RGB bitmap images. This algorithm can be used to protect property rights to multimedia resources in which it is impossible to use ordinary watermarks due to the impossibility of changing the image (such as medical data where high accuracy is required and the appearance of artifacts is unacceptable) or due to the presence of a higher distortion of the container. This algorithm is based on DWT, SVD and operations in the field by modulo 256. The software implementation of the algorithm was developed (using the Accord and *** libraries to implement DWT, SVD). The software implementation of the algorithm was tested. This algorithm has advantages in the form of normalization of the average error, but it needs further research to improve its performance.

关键词： Software algorithms Authentication Public key Watermarking Distortion Software Libraries Discrete wavelet transforms Faces Testing

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Metasystems in the Strategic Management of the Region

Metasystems in the Strategic Management of the Region

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Alexander Solomatin Department of Mathematical Methods of Regional Programming Federal Research Center “Computer Science and Control” of RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

Instead of the traditional “system-environment” pair for objects of the regional economy, it is proposed to consider metasystems - these objects together with all interacting objects of the microenvironment. Each object is considered as a point in the multidimensional space of characteristics. Objects are visualized to reflect their development and interaction with other objects.

关键词： Visualization Reflection Large-scale systems

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Runtime Verification of Autonomous Systems Utilizing Digital Twins as a Service 5

Runtime Verification of Autonomous Systems Utilizing Digital...

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5th IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2024

作者： Kristensen, Morten Haahr Bonizzi, Alberto Gomes, Claudio Hansen, Simon Thrane Isasa, Carlos Iven, Hannes Kamburjan, Eduard Larsen, Peter Gorm Leucker, Martin Talasila, Prasad Tang, Valdemar Trojgard Tonetta, Stefano Vosteen, Lars B. Wright, Thomas Aarhus University Department of Electrical and Computer Engineering Denmark Fondazione Bruno Kessler Italy University of Luxembourg Interdisciplinary Centre for Security Reliability and Trust Luxembourg Institute for Software Engineering and Programming Languages Universität zu Lübeck Germany University of Oslo Department of Informatics Norway

ISBN: (纸本)9798350389760

Autonomous Systems (AS) enable systems to adapt to drastic and unprecedented environmental changes, a capability that can be enhanced through the utilization of Digital Twins (DTs). However, the additional capabilities of AS come at the cost of explainability, as the expanding adaptation space complicates the reasoning about the system's behavior. For certain types of systems, it is crucial to ensure that specific properties are upheld despite the system's autonomous behavior. To facilitate the monitoring of these properties, we propose the use of Runtime Verification (RV). This tutorial demonstrates the integration of RV tools into the Digital Twins as a Service (DTaaS) platform to monitor and verify the behavior of AS in real-time. By exploring various methods to incorporate RV tools within a DT context, the tutorial aims to advance the application of RV technologies in autonomic computing and self-adaptive system design. Specifically, we demonstrate how the behavior of a self-configuring DT can be verified utilizing RV. This is accomplished through the DTaaS platform, which supports seamless deployment of DT-based AS. © 2024 IEEE.

关键词： Adaptive systems

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Human VS AI-Generated Content: Where to Draw the Line?

Human VS AI-Generated Content: Where to Draw the Line?

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International Scientific Conference Electronics (ET)

作者： Daniela V. Minkovska Elena V. Antonova Department of Programming and Computer Technologies Faculty of Computer Systems and Technologies Technical University of Sofia 8 Kliment Ohridski blvd. Sofia Bulgaria

ISBN: (数字)9798350376449

ISBN: (纸本)9798350376456

The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential and constraints of such technology. A study was conducted with students at the Technical University of Sofia, to assess their ability to distinguish between texts written by humans and AI. The results showcase that learners need to develop their critical analysis skills evidenced by their mixed expertise.

关键词： Ethics Virtual assistants Education Artificial intelligence Standards

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Optimistic Versioning for Conflict-tolerant Collaborative Blended Modeling 10

Optimistic Versioning for Conflict-tolerant Collaborative Bl...

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STAF 2022 Workshop: 10th International Workshop on Bidirectional Transformations, BX 2022, 2nd International Workshop on Foundations and Practice of Visual Modeling, FPVM 2022 and 2nd International Workshop on MDE for Smart IoT Systems, MeSS 2022

作者： Exelmans, Joeri Pietron, Jakob Raschke, Alexander Vangheluwe, Hans Tichy, Matthias Department of Computer Science University of Antwerp - Flanders Make Antwerp Belgium Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

Optimistic versioning is a key component in supporting collaborative workflows. Text-based versioning has been widely adopted for versioning code, but in model-driven engineering, dealing with visual concrete syntaxes, new methods are required. In the case of blended modeling, a mixture of both textual and visual syntaxes, concurrently editable and synchronizable, introduces additional challenges. We propose a type of operation-based versioning to record not only user edits, but also bi-directional change propagations between concrete and abstract syntax. This way we can support blended modeling with layout continuity, and flexible handling of missing information (e. g., layout information) when rendering changes from abstract to concrete syntax. In addition, the proposed versioning approach enables collaborative conflict resolution by allowing partial conflict resolution, thus deferring a final resolution. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Abstracting

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