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4th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2022

作者： Tsao, Yung-Chung Kuo, Yaw-Wen Wu, Chia-Chun Tsai, Yin-Te Hsu, Chihcheng Ho, Liulin Wang, Han-Ching National Chi Nan University Dep. of Electrical Engineering Nantou County Taiwan National Quemoy University Dep. of Industrial Engineering and Management Kinmen County Taiwan Providence University Dep. of Computer Science and Communication Engineering Taichung City Taiwan National Central University Dep. of Information Management Taoyuan Country Taiwan College of Science and Technology National Chi Nan University Nantou County Taiwan Xinhe Elementary School Xindian District New Taipei City Taiwan

ISBN: (数字)9781728195797

ISBN: (纸本)9781728195797

More home appliances were designed and manufactured in the market, but fewer commercial products related to water-flow monitoring are sold in the current market. Water-related costs and expenses are cheaper than others, but water is one of the critical survival necessities for human beings. Thus, the home appliances or the smart home needs to pay attention to ubiquitous water resources as one of the limited natural earth resources. We follow the above-mentioned issues to achieve an internet of things (IoT) based architecture to design a flow-monitoring information collecting device (FMICD). Hall sensors were used to collect the water-flow consumption and to upload the information of the environment monitor system which was implemented in the previous research. In the proposed architecture, the FMICDs are designed and developed with the MCU-based controller binding to a water-flow meter (Model: YF-S201) equipped to monitor water consumption. We implemented FMICDs in the Xinhe Elementary School in the Xindian District of New Taipei City in Taiwan to validate the usability and feasibility of the study with a website (http://***:9999/***) to offer related users and staff to validate the usability in the study. © 2022 IEEE.

关键词： Internet of things

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TIoT: A Trust by Design Architecture for Secure and Private Internet of Things (IoT) 21

TIoT: A Trust by Design Architecture for Secure and Private ...

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21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Alsheakh, H. Mahdi, Tareq Nasser Kadhm, Mustafa S. Al Shammari, Abeer Abdulsahib, Fatimah I. Taher, Hazeem B Algriree, Waleed Alobaidi, Marwa Q. Mohammed, Hayder Dhafer College of Science Mustansiriyah University Department of Computer Science Baghdad Iraq College of Pharmacy Mustansiriyah University Clinical Laboratory Science Baghdad Iraq Ministry of Science and Technology Baghdad Iraq Szechenyi Istvan Egyetem Department of Computer Science Gyor9026 Hungary University of Thi-Qar Department of Computer Science Thi-Qar Iraq University Putra Malaysia Dep. of Wireless Communication and Network Engineering Selangor Malaysia National Engineering School of Sfax Sfax University Sfax Tunisia College of Pharmacy Mustansiriyah University Baghdad Iraq

ISBN: (纸本)9798350374131

The Internet of Things (loT) facilitates the interconnection of a vast array of devices, services, and individuals for data exchange in multi-domain loT ecosystems, the social, physical, and cyber domains. That emerges various security, privacy, and trust issues, such as vulnerabilities, threats, and attacks. Addressing these challenges requires innovative solutions. New controls (solutions) are needed. Trust by design can be one of these controls, supporting security and privacy (among other system components). This paper proposes a Trusted loT (TloT), a trust-by-design model, and highlights the author's principal contributions. First, it advocates for implementing Tlo T through trust services. Second, it outlines an architecture for using trust by design in loT, including the design of its top-level structure and activities. Minor contributions include overviews of loT and trust, as well as looking at security and privacy in terms of security services and privacy services, respectively. © 2024 IEEE.

关键词： Internet of things

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A Bayesian take on Gaussian process networks 23

A Bayesian take on Gaussian process networks

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Enrico Giudice Jack Kuipers Giusi Moffa Dep. of Mathematics and Computer Science University of Basel Basel Switzerland Dep. of Biosystems Science and Engineering ETH Zurich Basel Switzerland Dep. of Mathematics and Computer Science University of Basel Basel Switzerland and Division of Psychiatry University College London London UK

Gaussian Process Networks (GPNs) are a class of directed graphical models which employ Gaussian processes as priors for the conditional expectation of each variable given its parents in the network. The model allows the description of continuous joint distributions in a compact but flexible manner with minimal parametric assumptions on the dep.ndencies between variables. Bayesian structure learning of GPNs requires computing the posterior over graphs of the network and is computationally infeasible even in low dimensions. This work implements Monte Carlo and Markov Chain Monte Carlo methods to sample from the posterior distribution of network structures. As such, the approach follows the Bayesian paradigm, comparing models via their marginal likelihood and computing the posterior probability of the GPN features. Simulation studies show that our method outperforms state-of-the-art algorithms in recovering the graphical structure of the network and provides an accurate approximation of its posterior distribution.

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Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AI

Designing Participatory AI: Creative Professionals' Worries ...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing systems, CHI EA 2023

作者： Inie, Nanna Falk, Jeanette Tanimoto, Steve It University of Copenhagen Copenhagen Denmark Dep. of Artificial Intelligence and Human Interfaces University of Salzburg Salzburg Austria Paul G. Allen School of Computer Science & Engineering University of Washington Seattle United States

ISBN: (纸本)9781450394222

Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. Such technologies potentially introduce a massive disruption to creative fields. This paper presents the results of a qualitative survey (N = 23) investigating how creative professionals think about generative AI. The results show that the advancement of these AI models prompts important reflections on what defines creativity and how creatives imagine using AI to support their workflows. Based on these reflections, we discuss how we might design participatory AI in the domain of creative expertise with the goal of empowering creative professionals in their present and future coexistence with AI. © 2023 Owner/Author.

关键词： computer programming

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A Bayesian Take on Gaussian Process Networks

arXiv

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arXiv 2023年

作者： Giudice, Enrico Kuipers, Jack Moffa, Giusi Dep. of Mathematics and Computer Science University of Basel Basel Switzerland Dep. of Biosystems Science and Engineering ETH Zurich Basel Switzerland Dep. of Mathematics and Computer Science University of Basel Basel Switzerland Division of Psychiatry University College London London United Kingdom

关键词： Approximation algorithms

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Deep Feature Extraction Framework Based on DNN for Enhancing Mirai Attachment Classification in Machine Learning

Deep Feature Extraction Framework Based on DNN for Enhancing...

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Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Hasan Gharaibeh Mohammad Aljaidi Ahmad Nasayreh Qais Al-Na'amneh Ameera S. Jaradat Ghassan Samara Rabia Emhamed Al Mamlook Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan Dep. of Business Administration Trine University Indiana USA Department of Mechanical and Industrial Engineering University of Zawia Tripoli Libia

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

Nowadays, the rapid growth of Internet of Things (IoT) devices has changed many parts of our lives by providing seamless connectivity and automation. However, this expansion has created new challenges and vulnerabilities, especially with regard to security. Mirai botnet, a strain of malware that has severely damaged the IoT ecosystem, is one of the prominent risks to IoT security. This research examines the impact of the Mirai botnet on IoT devices. In this study, we present a hybrid model to detect Mirai attacks. Deep neural networks (DNNs) are used to extract significant deep features, which are subsequently passed to the (Light Gradient Boosting Machine) LGBM algorithm for classification. A dataset from the Canadian Institute 2023 that included several kinds of Internet of Things assaults was used to assess the model. The model achieved excellent feature extraction and promising results with accuracy, recall, precision, and F1-score scoring up to 95 % for all. These accuracy results demonstrated the superior performance of the suggested model over competing techniques, which had scores of 71 %, 85%, and 52%, respectively, for Support Vector Machine (SVM), Light Gradient Boosting Machine (LGBM), and Stochastic Gradient Descent (SGD). Furthermore, the model outperforms the DNN model, which received a score of 65%.

关键词： Support vector machines Accuracy Machine learning algorithms Botnet Artificial neural networks Feature extraction Boosting

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Machine Learning-Enhanced Standard Deviation to Detect and Handle of Outlier in the 3D Point-Cloud Data

Machine Learning-Enhanced Standard Deviation to Detect and H...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Mohammad Rasoul Tanhatalab Manuel Forrer Michael Nelz Dep. of Information Engineering and Computer Science Trento University Italy ferrisol Co Graz Austria Nelo Intelligence Eichenau Germany

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

Outlier removal is an important step in 3D point cloud data processing. Various methodologies for outlier removal will be analyzed shortly in this paper by describing a range of statistical and machine-learning techniques. Thus, the intent is to analyze different techniques and evaluate their performance in order to justify unique advantages and limitations of each technique. These limitations and advantages advance the discussion by introducing a new approach combining statistical and machine learning techniques on a real-world dataset. It not only identifies the spatial position of outliers but also enhances the measurement precision at those specific points. This work has a lot of significance from many aspects for researchers, engineers, and practitioners. Especially in robotics, industrial processes, augmented reality, and autonomous driving, the nature of 3D point cloud data requires sophisticated outlier handling. We believe our work will serve as a reference to optimize data quality in these dynamic applications under development.

关键词： Point cloud compression Three-dimensional displays Filtering Statistical analysis Service robots Machine learning Signal processing Position measurement Mathematical models Standards

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An Efficient Quantum cryptanalysis of lightweight hash function - PHOTON-Beetle 2

An Efficient Quantum cryptanalysis of lightweight hash funct...

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2nd International Conference on Automation, Computing and Renewable systems, ICACRS 2023

作者： Allu, Swamy Naidu Tentu, Appala Naidu Kancharla, Gangadhara Rao Dep. of Computer Science & Engineering Acharya Nagarjuna University Andhra Pradesh Guntur522510 India CR Rao AIMSCS UoH Campus Telangana Hyderabad500046 India CR Rao Advanced Institute of Mathematics Statistics and Computer Science University of Hyderabad Campus Telangana Hyderabad500046 India

ISBN: (纸本)9798350340235

Quantum cryptanalysis methods are used to crack the majority of symmetric key ciphers. With this knowledge, cryptologists should be able to create post-quantum symmetric ciphers by incorporating these new quantum cryptanalysis techniques into their toolkit. Secure communication is crucial for applications related to the Internet of Things (IoT) to avoid cyberattacks. Cryptographic hash functions can be used to protect data integrity. The development of large-scale, fault-tolerant quantum computers is the most significant challenge. Recent techniques to attack symmetric key schemes can be achieved by using the Pre-image attack method, Simon’s algorithm, or by combining Simon’s and Grover’s algorithms. In this study, we explored some of the most recent methods for quantum cryptanalysis of symmetric key ciphers. Firstly, we discussed the design of quantum cryptanalysis methods, along with the advantages over classical procedures. In this paper, we illustrate the implementation of the NIST-standard lightweight hash function PHOTON-Beetle on a Quantum computer (using IBM Qiskit), which is mostly used in IoT devices. Efficient quantum implementation of PHOTON-Beetle is proposed in this paper. This paper calculates the quantum cost of PHOTON-Beetle for every layer and compares it with [1]. © 2023 IEEE.

关键词： IoT PHOTON-Beetle Post-quantum cryptography Quantum algorithms Quantum cryptanalysis Symmetric cryptanalysis

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Bi2S3 and NiBiS3 electrocatalysts for alkaline hydrogen evolution reactions

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International Journal of Hydrogen Energy 2025年

作者： Aksaray, Goncagül Mert, Mehmet Erman Mert, Başak Doğru Kardaş, Gülfeza Çukurova University Arts and Sciences Faculty Chemistry Dep. Adana01330 Turkey Adana Alparslan Türkeş Science and Technology University Advanced Technology Research and Application Center Adana01250 Turkey Adana Alparslan Türkeş Science and Technology University Engineering Faculty Energy Systems Engineering Dep. Adana01250 Turkey

Developing efficient and available catalysts is important for advancing hydrogen evolution reaction (HER) in alkaline water electrolysis, a promising technology for sustainable hydrogen production. This study reports the synthesis and electrochemical performance of Bi2S3 and NiBiS3 catalysts for the HER in alkaline water electrolysis. The catalysts were prepared via a hydrothermal method and characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX). The electrochemical behavior was evaluated using cyclic voltammetry (CV), cathodic current-potential curves (Tafel polarization), electrochemical impedance spectroscopy (EIS), and chronoamperometry (CA) in 1 M KOH. The graphite electrode modified with NiBiS3 exhibited high catalytic activity. The significant increase in current density and decrease in polarization resistance from 3000 Ω cm2 (bare graphite) to 18.55 Ω cm2 were detected. The G/NiBiS3 electrode outperformed both the bare graphite and G/Bi2S3 electrodes, with the current density reaching −2.3 × 10−3 A cm−2 at −0.26 V. Morphological analysis revealed that Bi2S3 forms flower-like structures, while NiBiS3 exhibits a cauliflower-like morphology, providing increased active surface areas important for catalytic activity. The Tafel slope analysis confirmed the Volmer step as the rate-determining step in the HER mechanism, with the adsorbed hydrogen subsequently forming molecular hydrogen. Stability testing through CA demonstrated consistent catalytic activity, with the current density maintained at −0.014 A cm−2 over 75000 s. These findings demonstrate the potential of NiBiS3 as a reliable and effective catalyst for alkaline electrolysis-based sustainable hydrogen production. © 2025

关键词： Cyclic voltammetry

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Towards Unveiling Vulnerabilities and Securing IoT Devices: An Ontology-Based Approach

Towards Unveiling Vulnerabilities and Securing IoT Devices: ...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Mukund Bhole Wolfgang Kastner Thilo Sauter TU Wien Institute of Computer Engineering Vienna Austria Dep. of Integrated Sensor Systems TU Wien Institute of Computer Technology Danube University Krems Austria

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

In the rapidly expanding landscape of Internet of Things (IoT), sensors have emerged as pivotal components, playing a critical role in sensing and data collection. However, this crucial function also renders them susceptible to potential threats such as unauthorized access and security breaches. This paper investigates the vulnerabilities that lead to these threats and offers a comprehensive set of best practices aimed at fortifying the security of IoT devices. We highlight key measures such as secure device design, robust authentication mechanisms, encrypted communication protocols, regular updates, and emphasize the importance of collaborative efforts among stakeholders using an ontological approach. An Ontology provides a structured framework for organizing knowledge, facilitating clearer communication, efficient data management, and enhanced decision-making. Thus, this paper contributes to the development of a more secure and resilient IoT ecosystem.

关键词： Protocols Ecosystems Collaboration Authentication Ontologies Sensors Internet of Things Stakeholders Cryptography Best practices

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