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Machine Learning and Autonomous systems (ICMLAS), International Conference on

作者： Sahar Ebadinezhad Nooshin Nooraei Nia Nasratullah Shirzad Nwabueze Kenneth Osemeha Department of Computer Information Systems Computer Information Systems Research and Technology Center (CISRTC) Near East University Nicosia Turkey Artificial Intelligence Near East University Nicosia North Cyprus Software Engineering Department Near East University Nicosia North Cyprus

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Due to The lack of comparison studies and practical applications of RNN, LSTM, and hybrid RNN-LSTM models for intrusion detection systems, especially when managing class imbalances in complex network datasets, represents a gap in the literature. This study investigates the application of deep learning techniques to improve the detection capabilities of IDS. For this study, we applied and assessed Recurrent Neural Network, Long Short-Term Memory, and Hybrid RNN-LSTM models on a UNSW-NB15 dataset, and to redress class imbalance we trained and validated our models using synthetic minority over-sampling. The RNN-LSTM model was shown to perform the best with a 9 4. 0 0 % accuracy in comparison to other models. These experimental results signify the possibility of enhancing IDS performance and a dependable method of detecting various network intrusions with the use of hybrid models comprised of RNN & LSTM.

关键词： Deep learning Recurrent neural networks Accuracy Computational modeling Intrusion detection computer architecture Network security Hyperparameter optimization Network intrusion Long short term memory

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Control of Multipath Transmissions in the Nodes of Switching Segments of Reserved Paths 6

Control of Multipath Transmissions in the Nodes of Switching...

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6th International Scientific Conference on Information, Control, and Communication Technologies, ICCT 2022

作者： Bogatyrev, Vladimir A. Bogatyrev, Stanislav V. Bogatyrev, Anatoly V. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia Yadro Cloud Storage Development Center Saint Petersburg Russia

ISBN: (数字)9781665493673

ISBN: (纸本)9781665493673

The options for ensuring timely delivery of packages to the addressee in networks with duplication of communication paths with the addressee for some subscribers are analyzed. Connecting subscribers to two communication routes with the addressee allows you to load-balance routes and carry out duplicated transmissions aimed at increasing the probability of delivering at least one copy of the transmitted packet in the required time. The possibilities of using route switch nodes for traffic management and replication of transmitted packets are analyzed. At the same time, two variants of duplicated transmissions are considered. For the first option, new replicas and ways of their transmission to the addressee are formed in one of the nodes connecting the existing paths by the first accepted replica. The replica coming in second is destroyed. For the second option, changing the transmission paths of replicas generated from the source in the nodes linking the paths is not carried out. The area of effectiveness of the proposed variants of duplicated transmissions is shown. The influence of the location of route switches on the timeliness of package delivery from subscribers connected to one or two communication paths with the addressee is investigated. The existence of an optimal arrangement of route switches is shown. © 2022 IEEE.

关键词： Real time control

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Research and development of two-factor authentication methods using neural networks 4

Research and development of two-factor authentication method...

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4th IEEE International Conference on Smart Information systems and Technologies, SIST 2024

作者： Darbek, Temirkhan Mukasheva, Assel Bissembayev, Alibek Gnatyuk, Sergiy Mukammejanova, Dinargul The Department of Information Systems and Cybersecurity Almaty university of power engineering and telecommunications Almaty Kazakhstan The School of Information Technology and Engineering Kazakh-British Technical University Almaty Kazakhstan The School of Information Technology and Engineering Kazakh British Technical University Almaty Kazakhstan The Faculty of Cybersecurity Computer and Software Engineering at National Aviation University National Aviation University Kyiv Ukraine The Department of Artificial Intelligence and Big Data Kazakh National University named after Al-Farabi Almaty Kazakhstan

ISBN: (纸本)9798350374865

This article is devoted to the research and development of innovative two-factor authentication (2FA) methods using neural networks. 2FA plays a key role in ensuring the security of data and accounts in the modern digital world, and the use of neural networks opens up new prospects in strengthening protection and improving the user experience. The article presents an analysis of existing 2FA methods, identifies their limitations, and discusses the advantages of using neural networks in this area. The main focus is on the development of new authentication algorithms based on deep learning, providing effective anomaly detection and support for a dynamic adaptive approach. In the context of the article, the issues of privacy and data security are also considered, as well as the possibilities of applying the developed methods in various fields, including finance, medicine and the Internet of Things. The results of the study represent a significant contribution to the field of digital. © 2024 IEEE.

关键词： biometric authentication deep learning digital security identification Neural networks

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Choosing the Discipline of Restoring computer systems with Acceptable Degradation with Consolidation of Node Resources Saved After Failures 6

Choosing the Discipline of Restoring Computer Systems with A...

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6th International Scientific Conference on Information, Control, and Communication Technologies, ICCT 2022

作者： Bogatyrev, Vladimir A. Bogatyrev, Stanislav V. Bogatyrev, Anatoly V. Security Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Saint Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia Yadro Cloud Storage Development Center Saint Petersburg Russia

ISBN: (数字)9781665493673

ISBN: (纸本)9781665493673

An approach to substantiating the choice of a discipline for the maintenance of a redundant computer system, with the possible use of node resources saved after failures, is considered. The choice is aimed at improving the reliability and profitability of the system, taking into account the operational costs of restoring nodes. Models of reliability of systems with service disciplines are proposed, providing both the possibility of immediate recovery of nodes after failures, and allowing degradation of the system when using node resources stored after failures in it. The models take into account the conditions of the admissibility or inadmissibility of the loss of information accumulated during the operation of the system. The operating costs are determined, taking into account the costs of restoring nodes for the system maintenance disciplines under consideration © 2022 IEEE.

关键词： Fault tolerance

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Chaotification as a Method for the Treatment of Uncertainty

Chaotification as a Method for the Treatment of Uncertainty

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2021 International Conference on Data Science and Its Applications, ICoDSA 2021

作者： Benderskaya, Elena N. Great St. Petersburg Polytechnic University Computer Systems and Software Engineering Department St. Petersburg Russia

ISBN: (纸本)9781665443036

Chaotification of the systems is considered as a method for the implementation of the 'order-chaos' boundary computations. A natural phenomenon of the adaptation mechanism provided by self-organization is used for the treatment of uncertainty. Under consideration is the uncertainty dealing with the object model stricture or the object's environment model stricture and the uncertainty dealing with the object model parameters or the object's environment model parameters. Due to the nonlinear dynamic, it is possible to obtain a universal and adequate structure that resolves the complex problem dealing with uncertainty. The proposed approach is based on the idea of the original expansion of the solution space with additional dimensions. The possibilities of the synergetics and chaos theory for problem-solving in the area of computer Science and systems Science are discussed. The potential of chaotic systems to uncertainty resolution by self-organization and synchronization is demonstrated by the example of clustering in the condition of full uncertainty. An illustrative example of the proposed approach to solve the clustering problems without information about the number of clusters and information about specific data topology is presented. A comparison of the classical approaches and the proposed is given. Also, the features of the proposed approach and the further work are considered. © 2021 IEEE.

关键词： Chaotic systems

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University Distributed computer Network Vulnerability Assessment

University Distributed Computer Network Vulnerability Assess...

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2023 IEEE International Conference on Smart Information systems and Technologies, SIST 2023

作者： Lakhno, Valerii Malyukov, Volodimir Akhmetov, Bakhtyzhan Yagaliyeva, Bagdat Kryvoruchko, Olena Desiatko, Alona National University of Life and Environmental Sciences of Ukraine Department of Computer Systems Networks and Cybersecurity Kyiv Ukraine Abai Kazakh National Pedagogical University Department of Informatics and Informatization of Education Almaty Kazakhstan Department of Software Engineering and Cybersecurity State University of Trade and Economics Kyiv Ukraine

ISBN: (纸本)9798350335040

A methodology for evaluating information security (IS) for a distributed computer network (DCN) of a university (hereinafter referred to as UDCN) has been proposed. A mathematical model for calculating the UDCN vulnerability factor has been presented. The UDCN vulnerability coefficient makes it possible to assess its IS level at the UDCN design stage. The results of simulation modeling and virtualization of IS UDCN components have also been presented. In the course of simulation modeling, a model of a protected UDCN was designed and tested. In the experimental UDCN model, the network devices selected in the course of modeling the vulnerability coefficient were emulated on virtual machines (VMs). UDCN resources were reproduced using the Proxmox VE virtualization system. On the UDCN hosts running PVE, the Suricata Intrusion Detection System (IPS) was used. Splunk was used as SIEM. © 2023 IEEE.

关键词： Intrusion detection

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Optimizing Link-Identified Forwarding Framework in LEO Satellite Networks 21

Optimizing Link-Identified Forwarding Framework in LEO Satel...

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21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Zhang, Hefan Wang, Zhiyuan Zhang, Shan Meng, Qingkai Luo, Hongbin School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China Institute of Artificial Intelligence Beihang University Beijing China State Key Laboratory of Software Development Environment China State Key Laboratory of Virtual Reality Technology and Systems China

ISBN: (纸本)9783903176553

Low earth orbit (LEO) satellite networks have the potential to provide low-latency communication with global coverage. To unleash this potential, it is crucial to achieve efficient data delivery. In this paper, we analyze the topology characteristics of LEO satellite networks, and propose a source-route-style forwarding framework. Specifically, we leverage the deterministic neighbor relationship and identify all the unidirectional inter-satellite links (ISLs). Moreover, our framework utilizes the in-packet bloom filter (BF) to store the source-route-style forwarding information. This way, the source satellite could encode multiple ISL identifiers into the BF, which actually specifies the forwarding path. The intermediate satellites only need to check whether the outgoing ISLs are encoded and forward packets accordingly. Due to false positives caused by BF, the more ISLs are encoded at a time, the more redundant forwardings emerge. To reduce forwarding overhead, we take into account segment encoding, allowing the source and intermediate satellites to encode part of ISLs towards the destination. Overall, segment encoding seeks the right balance between forwarding overhead and encoding delay. We characterize a wide range of segment encoding policy in a unified framework, and derive the expected forwarding overhead in a closed-form. The segment encoding design is formulated as a binary non-linear programming, which is NP-hard. To overcome the challenge, we leverage its decomposable structure, and propose an efficient algorithm to solve it optimally. Finally, we validate our analytical results via packet-level experiments. Results also show that our proposed segment encoding policy significantly reduces the queuing delay compared to source encoding. © 2023 IFIP.

关键词： Satellites

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Deep Learning-Based Audio Splicing Forgery Detection Using PVTv2 Transformer

Deep Learning-Based Audio Splicing Forgery Detection Using P...

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Innovations in Intelligent systems and Applications Conference

作者： Elif Kanca Tolgahan Gulsoy Arda Ustubioglu Beste Ustubioglu Selen Ayas Elif Baykal Kablan Guzin Ulutas Department of Software Engineering Karadeniz Technical University Trabzon Turkey Department of Management Information Systems Trabzon University Trabzon Turkey Department of Computer Engineering Karadeniz Technical University Trabzon Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

Attacks on multimedia files by malicious users have become quite common, especially with the increase in the number of editing tools and their ease of use. Considering that such files can now be used both as evidence and for social visibility in all kinds of environments, it has become important to prove their authenticity. With the proposed method, the detection of merging forgeries in audio files has been carried out. For this purpose, the audio files received from the input are converted into cochleagram images. The PVTv2 based deep network architecture is trained with the generated cochleagram images. As a result of the training, the suspicious audio file given as input is labelled as original/fake. The proposed method gives 96.11% accuracy for 2s database, 94.63% accuracy for 3s database and 95.19% accuracy for 2s-3s database.

关键词： Training Technological innovation Accuracy Databases Splicing Network architecture Transformers Forgery Security Reliability

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Uvlhub: A Feature Model Data Repository Using Uvl and Open Science Principles

SSRN

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SSRN 2023年

作者： Romero-Organvidez, David Galindo, José A. Sundermann, Chico Horcas, Jose-Miguel Benavides, David Department of Computer Languages and Systems University of Seville Spain Institute of Software Engineering and Programming Languages Ulm University Germany CAOSD ITIS Software University of Málaga Spain

Feature models are the de facto standard for modelling variabilities and commonalities. Concrete models in different domains exist;however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serialising feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents UVLHUB, a repository of feature models in UVL format. UVLHUB provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo providing a permanent save of datasets and following open science principles. UVLHUB includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling. © 2023, The Authors. All rights reserved.

关键词： Concretes

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Empowering Personalized Health Data Queries with Knowledge Graph and GPT-Enhanced Voice Assistant 25

Empowering Personalized Health Data Queries with Knowledge G...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Wang, Xin Ul Hasan, Wordh Li, Juan Hendawi, Rasha Du, Yang Xie, Bo Tao, Cui North Dakota State University Department of Computer Science Fargo United States Valley City State University Department of Computer Systems and Software Engineering Valley City United States School of Nursing The University of Texas at Austin Austin United States School of Biomedical Informatics University of Texas Health Science Center at Houston Houston United States

ISBN: (纸本)9798350330014

The proliferation of digital health technologies has led to an abundance of personal health data. However, querying and retrieving specific health-related information from disparate sources can be challenging and inconvenient, particularly for older individuals unfamiliar with technology. While ChatGPT offers a conversational interface, it lacks domain-specific knowledge, including personalized health information. To address this limitation, we present a novel approach that combines a knowledge graph and GPT to enable personalized health queries. Our solution utilizes a personal knowledge graph as a comprehensive knowledge source and fine-tunes GPT to provide accurate responses. We have implemented a voice assistant mobile app incorporating this knowledge graph-assisted GPT model and conducted initial feasibility testing. © 2023 IEEE.

关键词： Query processing

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