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Cryptochain approach to Cloud computing Security: Case study, Challenges, and Solutions 1

Cryptochain approach to Cloud Computing Security: Case study...

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1st international conference on advances in Computational science and Engineering, ICACSE 2020

作者： Mukherjee, Subham Sandane, Raghav Maharashtra Pune India Maharashtra Pune India

Cryptochain has attracted the new generation of FinTech technologies because of its disruptive security that adapts to teaching time. In particular, it provides security with peer-to-peer authentication, encryption, and hash generation. According to the FinTech sector, the security market's technology sector is predicted to grow to $ 20 billion at the end of 2021. With this, the cryptochain can operate across the whole Internet of Things (Cloud) ecosystem;its programs are predicted to expand. Cloud technology has been widely welcomed in all tech fields for its efficiency and reliability. This paper will discuss the theory of cryptochain technology and elated thermal research methods. We will learn how to sync cryptochain security on a cloud with its secure data solutions. © Published under licence by IOP Publishing Ltd.

关键词： Cloud computing

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Analysis of Safety-Critical Communication Protocols for On-Premise SIL4 Cloud in Railways 4th

Analysis of Safety-Critical Communication Protocols for On-P...

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4th international conference on Reliability, Safety, and Security of Railway Systems (RSSRail)

作者： Rother, Benjamin Golatowski, Frank Ansar, Zeeshan Kuzhiyelil, Don Resch, Stefan Hametner, Reinhard Pathak, Prashant Univ Rostock D-18051 Rostock Germany SYSGO GmbH Pfaffenstein 8 D-55270 Klein Winterheim Germany Thales Austria GmbH Handelskai 92 A-1200 Vienna Austria DB Netz AG Stresemannstr 123 D-10963 Berlin Germany

ISBN: (纸本)9783031058134;9783031058141

In this paper, we address the question of how SIL4 railway applications within on-premise cloud environments can communicate safely with internal and external systems. The EN 50159 standard is the railway standard applicable for safety-related communication. For IT/OT Security IEC 62443 can be considered. Most standardized protocols developed according to EN 50159 are peer-to-peer protocols involving two communication partners. To leverage the cloud environment, contemporary applications of other domains use a different communication scheme, namely publish-subscribe, to connect internal and external components and enable scalability. Based on this challenge, the goal of this paper is to investigate emerging communication protocols from different domains and their suitability for the railway system. We will first determine the requirements for the railway communication infrastructure and applications executed in a SIL4 cloud, i.e., an environment provided by on-premise data centers utilizing technologies such as virtualization and with other cloud-like features, such as scalability and flexible usage of resources. Furthermore, a brief comparison of the potential application-layer communication protocols from industrial domains with railway-specific safety-critical protocols will be presented. Finally, we will present a system architecture that demonstrates how safe communication can be realized by middleware protocols such as DDS or OPC UA and how they fulfill the previously established requirements for the railway system.

关键词： SIL4 Safety Railway SIL4 cloud Protocols Safe computing platform

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A Methodological Proposal to Foster the Development of Team Work Mediated by ICT in the Subject Software Engineering 17th

A Methodological Proposal to Foster the Development of Team ...

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17th Annual conference of the international-Association-of-Online-Engineering (IAOE) and the Global-Online-Laboratory-Consortium (GOLC) on Remote Engineering and Virtual Instrumentation (REV) - Cross Reality and data science in Engineering

作者： Granda Dihigo, Ailec Colome Cedeno, Dunia Maria Perez Pino, Maria Teresa Patterson Pena, Marisol de la Caridad Casar Espino, Liliana Argelia Diaz Bravo, Tito Univ Informat Sci Havana Cuba

ISBN: (纸本)9783030525750;9783030525743

The purpose of this study is to show some experiences in the methodological development of Software Engineering professors at the University of Informatics sciences by designing a set of group-work methodological and didactic actions, so that professors encourage their students to develop team work and collaborative learning with the help of ICT. The research methods employed were: analysis and synthesis, the systemic approach, the documentary analysis, interviews and scientific observations. A methodological procedure was developed based on the diagnostic analysis of the subject, taking into account the deficiencies from the previous course included in the reports. In this sense the development of teamwork and collaborative learning, using the means offered by ICT was included as a leading objective of the methodological work for the subject. The proposal was validated from the results gathered in the group interviews to professors who applied the set of actions, class observation guides, and the collaborative work developed in the virtual learning environment, as well as interviews to students to know their opinions about their professors performance. The design, development, and control of the actions integrating the methodological work contributed to the fulfillment of the research objective.

关键词： Methodological training Teamwork Collaborative learning Information and communication technologies (ICT)

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Reimagining Algorithmic Governance Cultural expressions and the negotiation of social imaginaries 22

Reimagining Algorithmic Governance Cultural expressions and ...

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12th Nordic conference on Human-Computer Interaction: Participative computing for Sustainable Futures, NordiCHI 2022

作者： Pötzsch, Holger Pereira, Gabriel UiT The Arctic University of Norway Norway Dept of Media and Communications London School of Economics and Political Science United Kingdom

ISBN: (纸本)9781450396998

This paper investigates the means through which a series of artistic works invite critical responses to algorithmic governance and the systems of surveillance and data capture these draw upon. In combining the theoretical frameworks of Cornelius Castoriadis, Jacques Ranciére, and Chantal Mouffe, we conceptualize how, and to what possible effects, art can engage politics and focus the discussion on concrete techniques through which selected works and performances question contemporary systems of algorithm-based management and control. Firstly, we offer an introduction to Cornelius Castoriadis's [13] theoretical framework regarding an imaginary institution and reproduction of society. So far, his concepts have been treated in a rather metaphorical manner in the literature on algorithmic governance and we set out to provide a thorough theoretical grounding of this valuable framework. We then add Jacques Ranciére's [49, 51] concept of a distribution of the sensible and draw upon Chantal Mouffe's [47] theories of art, democracy, and hegemony to account for art's political function. As a second step, we focus on specific media artworks that respond to concrete instances of algorithmic governance by defamiliarizing and transgressing received social imaginaries to enable an active reshaping of received technologies and sedimented practices. We identify and illustrate a selection of tactics available to artists to question and contain these increasingly automated systems;including appropriating, rejecting, inverting (perspectives, scales, values/norms), and creating alternatives. We show how these tactics are deployed to invite a subversion and reimagination of dominant algorithmic imaginaries and the specific frames of sensing, speaking, and doing they imply. Our objective is to give an overview of available artistic tactics, and to facilitate further research of, and critical engagements with, algorithmic forms of governance and their enactments of surveillance and automat

关键词： Automation

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Fake News Detection in Low-Resource Languages 1st

Fake News Detection in Low-Resource Languages

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1st international conference on Speech and Language technologies for Low-resource Languages, SPELLL 2022

作者： Sivanaiah, Rajalakshmi Ramanathan, Nishaanth Hameed, Shajith Rajagopalan, Rahul Suseelan, Angel Deborah Thanagathai, Mirnalinee Thanka Nadar Department of Computer Science and Engineering Sri Sivasubramaniya Nadar College of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9783031332302

Fake news spreads much faster than real news. False information and misleading texts are the most important elements that lead to disasters and even life threats. One such strategy is fake news, which has become a never-ending phenomenon with the rise of the internet. There can be several devastating consequences due to fake news spreading. It is therefore important to prevent the spread of fake news. This paper shows how we prepared fake news data sets for a few low-resource languages and how we used Logistic Regression and BERT models to perform fake news classification in low-resource languages. Through rigorous experiments, we show that BERT-based-multilingual-cased and Logistic Regression models reach maximum F1 scores of around 98% and 95% respectively. We have done fake news classification with the models for low-resource Indian languages like Tamil, Kannada, Gujarati, and Malayalam. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Federated Learning with Blockchain: A Study of the Latest Decentralized Couple

Federated Learning with Blockchain: A Study of the Latest De...

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international conference on computing, Communication, and Intelligent Systems (ICCCIS)

作者： Arman Rasool Faridi Aiman Hafeez Faraz Masood Department of Computer Science Aligarh Muslim University Aligarh India

ISBN: (纸本)9781665462013

Federated learning is a method for machine learning that avoids the need to move data by training an algorithm in parallel on a large number of edge devices or servers that hold copies of the training data in their own memory. Conventional decentralized approaches often assume that local data samples are equally distributed, whereas typical centralized machine learning techniques involve uploading all local datasets to a single server. Federated learning has flaws like privacy and insufficient data. Blockchain’s rise offers a safe and effective method for Federated Learning implementation. In this paper, the collaboration of Federated learning and blockchain is discussed. Then the possible applications that can be developed using federated learning and blockchain are discussed. Furthermore, the challenges and opportunities for collaboration between these technologies are explained.

关键词： Training Privacy Machine learning algorithms Federated learning Collaboration Training data Blockchains

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Bug Recognition using Hybrid Fuzzy Logic algorithm and Support Vector Machine classification

Bug Recognition using Hybrid Fuzzy Logic algorithm and Suppo...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： K. Ananthi M. Balakrishnan M. Pandi N. Senthil Madasamy Artificial Intelligence &Data Science Dr.Mahalingam College of Engineering and Technology Coimbatore Tamil Nadu India Computer Science and Engineering Dr.Mahalingam College of Engineering and Technology Coimbatore Tamil Nadu India

In data mining and pattern recognition, the Support Vector Machine is an extensively used classification technique. The tuning weight methods and the distance of the metrics used in a Support Vector based classification system are important. The problem of determining the best feature weight values and measuring the distance between neighbors, which affects the Support vector machine's classification accuracy, is a key obstacle. For parameter optimization, a hybrid approach is applied in this paper. To quantify the equalities between thetraining data set and the test data set are observed and the similarity measuring approach known as the fuzzy distance metric is used. Additional work, such as creating a unique fuzzy membership function and membership degrees for each dataset, adds time to the design process for these hybrid systems. To improve the classification model's precision, this automated approach will heuristically explore the optimal bounds of fuzzy membership functions for each dataset. Additionally, looking into the optimal boundaries may decrease error rates and improve accuracy in the proposed system. The experimental results will be implemented into a real-world classification challenge sourced from the UCI machine-learning benchmark library.

关键词： Measurement Fuzzy logic Weight measurement Training Computer bugs Support vector machine classification Machine learning

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Review on Common IoT Communication technologies for Both Long-Range Network (LPWAN) and Short-Range Network 1st

Review on Common IoT Communication Technologies for Both Lon...

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1st international conference of Advanced computing and Informatics, ICACIN 2020

作者： Bahashwan, Abdullah Ahmed Anbar, Mohammed Abdullah, Nibras Al-Hadhrami, Tawfik Hanshi, Sabri M. GelugorPenang11800 Malaysia School of Science and Technology Nottingham Trent University Nottingham United Kingdom Seiyun Community College Hadhramaut Yemen

ISBN: (纸本)9789811560477

The Internet of Things refers to network of physical objects that use IP address for Internet connectivity and to communicate with other Internet-enabled devices and systems. The Internet of Things comes with a number of top-class applications and has also developed many things into smart devices. The enhanced objects would ultimately need to have better connectivity and wireless communication protocols with low power consumption. Hence, this chapter presents the survey which gives a picture of the current state of the art on conventional wireless technologies used in most IoT devices, as well as to select the most suitable common IoT communication technologies that can ensure uninterrupted connection and support real-time data transmission in energy efficient form. Also, this chapter contributed a comprehensive comparison for both long-range and short-range common IoT communication technologies that are used in different applications. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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A comprehensive survey of state-of-art techniques in digital watermarking

A comprehensive survey of state-of-art techniques in digital...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Sachin Allwadhi Kamaldeep Joshi Ashok Kumar Yadav Rainu Nandal Rishabh Jain Deptt. of Computer Science & Engg M.D.University Rohtak Haryana India Amity School of Engg. & Technology Amity University Noida U.P India Deptt. of Computer Science & Engg Galgotias College of Engineering and Technology Greater Noida India

Digital image watermarking refers to implanting secret information for copyright protection, content authentication of a given media to avoid future conflicts or illegal possession of data. A number of applications are present today for which suitable watermarking techniques can be used to mitigate this problem. Based on the domain, image watermarking can be categorized into spatial or transformation domains. Transform domain techniques are widely used by researchers because of their robustness and security. There is always a tradeoff between robustness, payload, and imperceptibility as maintained by various researchers that is also reviewed. Also, this paper presents various state-of-art watermarking techniques with their performance metrices such as PSNR, MSE, NC, BER, etc. along with their limitations. This survey help the researcher to develop a new watermarking model based on the application domain.

关键词： Digital images Computational modeling Authentication Watermarking Transforms Media Copyright protection

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Sentiment Analysis on Amazon Product Review

Sentiment Analysis on Amazon Product Review

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： B Kamalesh S. Vijayalakshmi Data Science Christ (Deemed to be University) Pune India

Users throughout the world may now access massive amounts of data thanks to the internet and social media platforms. [5] In every facet of human existence, electronic commerce (e-commerce) plays a crucial role. E-commerce is a marketing approach that enables businesses and consumers to buy and sell things via the internet. When buyers look for product information and compare alternatives online, they generally have access to dozens or hundreds of product reviews from alternative shoppers. Machine learning is the most appropriate approach to training a neural network in today’s age of practical artificial intelligence. So implementing a model to polarize those reviews and learn from them would make passing hundreds of comments a lot easier. [24] The interpretation will be a very basic product with positive, neutral, and negative polarization. The product is checked. This study suggests a sentiment evaluation model for shopper reviews based on the object and emotive word mining for emotional level analysis using machine learning approaches.

关键词： Training Sentiment analysis Analytical models Social networking (online) Computational modeling Neural networks Process control

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