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International Conference on distributed Computing systems Workshop

作者： Felix Kleinwort Wolf Posdorfer Janick Edinger Department of Computer Science Distributed Operating Systems University of Hamburg Hamburg Germany Department of Computer Science Computer Networks University of Hamburg Hamburg Germany

Bitcoin was released in 2008 as an electronic peer-to-peer payment system. The aim was to enable financial transactions in an anonymous manner between participating parties. However, Bitcoin is considered a pseudonymous network rather than anonymous, as the identity of the address owner is unknown, but every transaction is permanently stored on the Bitcoin blockchain and can be tracked by anyone. The structure of the blockchain, its transactions, and the Bitcoin network make it possible to deanonymize pseudonyms through various methods such as flow analysis, heuristics, and network traffic observations. Once a connection is established between pseudonyms used in the Bitcoin network and the real world, all previous transactions can be attributed to that identity. In 2021, Taproot was introduced to further increase privacy within the Bitcoin Network by introducing a new address format which will allow transactions to be more indistinguishable from one another. In this paper, we analyze current methods for deanonymizing Bitcoin transactions to understand which parts of the Bitcoin protocol they exploit. In addition, we look at the changes introduced by Taproot and determine the extent to which these changes affect the methods and what assumptions must be made for these methods to remain applicable.

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Int-BEB: Enhanced Binary Exponential Backoff using Q-learning

Int-BEB: Enhanced Binary Exponential Backoff using Q-learnin...

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International Conference on Pattern Analysis and Intelligent systems (PAIS)

作者： N. Zerguine Department of Computer Science Networks and Distributed Systems Laboratory Ferhat Abbas Setif 1 University Setif Algeria

Because of their development and success, MANETs are now preferred alternatives in many fields of study and application. The IEEE 802.11 standard is the basis of most wireless technologies. To treat collisions in wireless networks, IEEE 802.11 distributed Coordination Function (DCF) MAC layer employs Binary Exponential Backoff (BEB) algorithm, that is helpful in decreasing the potential of collision, but comes at the expense of several network performance metrics, such as medium access delay, bandwidth management, power use, and fairness. A Deep Learning technique called Deep Reinforcement Learning (DRL) allows an agent to communicate with the environment in order to accomplish a goal. In the present paper, we suggest Q-learning (QL), one of the DRL approaches to improve the Binary Exponential Backoff (BEB) in MANETs. The intelligently designed Int-BEB aims for better CW selection; this selection strikes to reduce collisions as much as possible and to give more chances to nodes that make collisions to access the channel by taking into consideration their residual energy. In-depth simulations are performed to evaluate the performance of the proposed mechanism. The performance of Int-BEB is evaluated in diverse networks with several criteria such as packet successful transmission, packet loss and energy.

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HTTP Flood DOS Attack Detection on Big Data Using Data Mining 1

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13th International Conference on Information systems and Advanced Technologies, ICISAT 2023

作者： Haddadi, Mohamed Khiat, Abdelhamid Abidi, Yasmina Derradji, Yaakoub Department of Commercial Sciences Faculty of Economic Commercial and Management Sciences M’hamed BOUGARA University of Boumerdes Independence Avenue Boumerdes35000 Algeria Networks and Distributed Systems Division Research Center on Scientic and Technical Information Ben Aknoun Algeria Department of Computer Science Faculty of Sciences University of Ferhat Abbas Setif1 Setif Algeria

ISBN: (数字)9783031605918

ISBN: (纸本)9783031605901

Nowadays, increasing use of Internet connection, security becomes a huge challenge for individuals as well as governments and organizations. Therefore, in the last decade, the world is moving towards green computing in the purpose either to store energy or to decrease operational costs. So, this new technology uses web servers to provide web applications to end user. Generally, these web servers become unavailable because of HTTP flood DoS attack. This paper applied data mining techniques such as WEKA and TANAGRA tools for data preprocessing in the aim to get a consistent data in one hand, and for classifying the traffic in normal behavior or anomaly using like J48, Random tree, SMO, Naïve bayes, IBK, and combined classifier in the other hand. For this aim, a well-known big data set is used which called http_csic_2010_full dataset. Results show that the two data mining tools are well close with all the classifiers, just MLP in WEKA, and CVM in TANAGRA they didn’t perform well in terms of detection accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： HTTP

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PpNNT: Multiparty Privacy-Preserving Neural Network Training System

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 370-383页

作者： Feng, Qi He, Debiao Shen, Jian Luo, Min Choo, Kim-Kwang Raymond Wuhan University School of Cyber Science and Engineering Wuhan430072 China Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou310018 China Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Matrix Elements Technologies Shanghai201204 China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

By leveraging smart devices [e.g., industrial Internet of Things (IIoT)] and real-time data analytics, organizations, such as production plants can benefit from increased productivity, reduced costs, enhanced self-monitoring, and autonomous decision-making. In such a setting, machine learning plays an important role in data analytics, but the use of conventional centralized machine learning solutions may raise uncomfortable concerns about data privacy. Hence, one can explore the use of federated learning. In this article, we propose privacy-preserving deep neural network training (PpNNT), which is designed to support federated learning in the multiparty setting. To minimize the overall costs, we further design a hybrid architecture to fully maximize resource utilization. Our proposed design allows the PpNNT system to provide high security, efficiency, and scalability for IIoT data analytics, as evidenced by our theoretical security proof and experimental results on the CIFAR10 dataset. © 2020 IEEE.

关键词： Decision making

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Enhancing load balancing & Fault Tolerance in Real-Time Applications Using SD-WAN

Enhancing load balancing & Fault Tolerance in Real-Time Appl...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Mohammed A. Makarem Akram Q. Algaolahi Abdullrhman A. Alhajri Muneef A Razaz Department of Computer Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Computer Networks and Distributed Systems Taiz University Taiz Yemen Department of Electriacl Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Wide Area networks (WANs) are critical components of modern network architecture, connecting multiple locations within an organization, enabling Internet access, and supporting real-time data sharing and high availability for applications and enterprises. Traditional WAN architectures often struggle with traffic management, fault tolerance, and real-time application delivery, leading to inefficiencies. To tackle these challenges, Software-Defined Wide Area Network (SD-WAN) technologies have emerged, offering greater agility, scalability, and network performance. This study introduces a methodological approach that utilizes Fortinet SD-WAN solution to evaluate the effectiveness of SD-WAN in enhancing load balancing and fault tolerance for real-time applications in small-scale organizations. The simulation results demonstrate that SD-WAN significantly improves network reliability and efficiency through dynamic traffic management and automatic failover mechanisms. This study underscores the potential of SD-WAN to provide superior performance compared to conventional networking solutions, making it a promising option for modern real-time applications.

关键词： Wide area networks Fault tolerance Fault tolerant systems Organizations Bandwidth Transforms Telecommunication traffic

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Assessing mowing intensity:A new index incorporating frequency,type of machinery,and technique

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Grassland Research 2024年第3期3卷 264-274页

作者： Margarita Hartlieb Sebastian Raubitzek Johanna L.Berger Michael Staab Juliane Vogt Manfred Ayasse Andreas Ostrowski Wolfgang Weisser Nico Blüthgen Ecological Networks Department of BiologyTechnical University of DarmstadtDarmstadtGermany SBA-Research ViennaAustria Natura 2000-Station Unstrut-Hainich/Eichsfeld Wildtierland Hainich gGmbHHörselberg-HainichGermany Institute of Evolutionary Ecology and Conservation Genomics Ulm UniversityUlmGermany Heinz Nixdorf Chair for Distributed Information Systems Faculty of Mathematics and Computer ScienceFriedrich Schiller UniversityJenaGermany Department of Life Science Systems School of Life SciencesTechnical University of MunichTerrestrial Ecology Research GroupFreisingGermany

Background:Only a few decades ago,colorful,small-scale,heterogeneous,and species-rich hay meadows or extensive pastures were common,but have often been replaced by species-poor,uniform,large-scale multicut *** advancements and improved efficiency in grassland management have come at the cost of ***:In Germany,150 grassland plots have been investigated since *** these extensive data,we propose a new compound index for estimating the site-specific mowing intensity in order to facilitate assessment of the impact of mowing intensity on biodiversity and ecosystem *** index integrates the various qualitative components of mowing machine type,mowing height and use of a conditioner,with the annual number of ***:The newly proposed index achieves a much finer gradation of mowing intensity compared to the previous quantification based on the number of cuts ***,a decrease in plant and arthropod species was observed at higher mowing ***:The proposed mowing intensity index offers enhanced precision in calculations and can easily be integrated into assessments of land-use intensity in ***,it could serve as a basis for providing subsidies to farmers,who adopt low-impact mowing practices.

关键词： applications conditioner mower mowing height number of cuts species richness

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A Communication-Induced Checkpointing Algorithm for Consistent-Transaction in distributed Database systems 1

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8th International Symposium on Security in Computing and Communications, SSCC 2020

作者： Mansouri, Houssem Pathan, Al-Sakib Khan Laboratory of Networks and Distributed Systems Computer Science Department Faculty of Sciences Ferhat Abbas Setif University 1 Setif Algeria Department of Computer Science and Engineering Independent University Dhaka Bangladesh

ISBN: (数字)9789811604225

ISBN: (纸本)9789811604218

For better protection of distributed systems, two well-known techniques are: checkpointing and rollback recovery. While failure protection is often considered a separate issue, it is crucial for establishing better secure distributed systems. This article is dedicated to the proposal of a new checkpointing algorithm for saving a consistent-transaction state in distributed databases ensuring that database management systems are able, after a failure, to recover the state of the database. The proposed communication-induced algorithm does not hamper the normal transaction processing and saves a global consistent-transaction state that records only the fully completed transactions. Analysis and experimental results of our proposal show that the proposed scheme saves a minimum number of forced checkpoints and has some performance gains compared to the alternative approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： distributed database systems

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Hybrid-MELAu: A Hybrid Mixing Engineered Linguistic Features Framework Based on Autoencoder for Social Bot Detection

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Informatica (Slovenia) 2022年第6期46卷 143-158页

作者： Hamida, Zineb Ferhat Refoufi, Allaoua Drif, Ahlem Giordano, Silvia Networks and Distributed Systems Laboratory Department of Computer Science University of Sétif 1 Sétif Algeria Networking Lab SUPSI University of Applied Sciences of Southern Switzerland Lugano Switzerland

Social bots are defined as computer algorithms that generate massive amounts of obnoxious or meaningful information. Most bot detection methods leverage multitudinous characteristics, from network features, temporal dynamics features, activities features, and sentiment features. However, there has been fairly lower work exploring lexicon measurement and linguistic indicators to detect bots. The main purpose of this research is to recognize the social bots through their writing style. Thus, we carried out an exploratory study on the effectiveness of only a set of linguistic features (17 features) exploitable for bot detection, without the need to resort to other types of features. And we develop a novel framework in a hybrid fashion of Mixing Engineered Linguistic features based on Autoencoders (Hybrid-MELAu). The semi-supervised Hybrid-MELAu framework is composed of two essential constituents: the features learner and the predictors. We establish the features learner innovated on two powerful structures: a) the first is a Deep dense Autoencoder fed by the Lexical and the Syntactic content (DALS) that represents the high order lexical and syntactic features in latent space, b) the second one is a Glove-BiLSTM autoencoder, which sculpts the semantic features;subsequently, we generate elite elements from the pre-trained encoder part from each latent space with transfer learning. We consider a sample of 1 Million from Cresci datasets to conduct our linguistic analysis comparison between the writing style of humans and bots. With this dataset, we observe that the bot's textual lexical diversity median is greater than the human one and the syntactic analysis based on speech-tagging shows a creative behavior in human writing style. Finally, we test the model's robustness on several public dataset (celebrity, pronbots-2019, and political bots). The proposed framework achieves a good accuracy of 92.22%. Overall, the results shown in this paper, and the related discussion, ar

关键词： Classification (of information)

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distributed AI in Zero-touch Provisioning for Edge networks: Challenges and Research Directions

arXiv

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arXiv 2023年

作者： Hazra, Abhishek Morichetta, Andrea Murturi, Ilir Lovén, Lauri Dehury, Chinmaya Kumar Pujol, Víctor Casamayor Donta, Praveen Kumar Dustdar, Schahram Department of Computer Science and Engineering the Indian Institute of Information Technology Sri City India Communications & Networks Lab Department of Electrical and Computer Engineering National University of Singapore Singapore119260 Singapore Distributed Systems Group TU Wien Vienna1040 Austria Center for Ubiquitous Computing University of Oulu 90014 Finland Institute of Computer Science University of Tartu Tartu51009 Estonia

Zero-touch network is anticipated to inaugurate the generation of intelligent and highly flexible resource provisioning strategies where multiple service providers collaboratively offer computation and storage resources. This transformation presents substantial challenges to network administration and service providers regarding sustainability and scalability. This article combines distributed Artificial Intelligence (DAI) with Zero-touch Provisioning (ZTP) for edge networks. This combination helps to manage network devices seamlessly and intelligently by minimizing human intervention. In addition, several advantages are also highlighted that come with incorporating distributed AI into ZTP in the context of edge networks. Further, we draw potential research directions to foster novel studies in this field and overcome the current limitations. Copyright © 2023, The Authors. All rights reserved.

关键词： Internet of things

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A Resilient Hierarchical Checkpointing Algorithm for distributed systems Running on Cluster Federation 1

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7th International Symposium on Security in Computing and Communications, SSCC 2019

作者： Mansouri, Houssem Pathan, Al-Sakib Khan Laboratory of Networks and Distributed Systems Computer Science Department Faculty of Sciences Ferhat Abbas Setif University 1 Sétif Algeria Department of Computer Science and Engineering Southeast University Dhaka Bangladesh

ISBN: (数字)9789811548253

ISBN: (纸本)9789811548246

In distributed systems, checkpointing method can be used to ensure fault-tolerance, which in turn could help the system’s security and stability. In simple terms, checkpointing means saving status information of a system. In this work, a novel hierarchical checkpointing algorithm for distributed systems is proposed, which runs on cluster federation. This algorithm is based on two well-known techniques in the literature and it ensures that a locally consistent state is always maintained in each cluster with a global optimistic logging technique between clusters. The proposed algorithm synchronizes the intra- and inter-cluster checkpointing process in such way that each checkpoint taken locally in any cluster is a segment of the consistent global state. Compared to other works, our scheme has low message cost as it makes sure that only few processes in each cluster record checkpoints for any execution operation. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Fault tolerance

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