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arXiv 2023年

作者： Li, Chao Palanisamy, Balaji Xu, Runhua Duan, Li Liu, Jiqiang Wang, Wei Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing China Department of Informatics and Networked Systems School of Computing and Information University of Pittsburgh Pittsburgh United States School of Computer Science and Engineering Beihang University Beijing China

Delegated-Proof-of-Stake (DPoS) blockchains, such as EOSIO, Steem and TRON, are governed by a committee of block producers elected via a coin-based voting system. We recently witnessed the first de facto blockchain takeover that happened between Steem and TRON. Within one hour of this incident, TRON founder took over the entire Steem committee, forcing the original Steem community to leave the blockchain that they maintained for years. This is a historical event in the evolution of blockchains and Web 3.0. Despite its significant disruptive impact, little is known about how vulnerable DPoS blockchains are in general to takeovers and the ways in which we can improve their resistance to takeovers. In this paper, we demonstrate that the resistance of a DPoS blockchain to takeovers is governed by both the theoretical design and the actual use of its underlying coin-based voting governance system. When voters actively cooperate to resist potential takeovers, our theoretical analysis reveals that the current active resistance of DPoS blockchains is far below the theoretical upper bound. However in practice, voter preferences could be significantly different. This paper presents the first large-scale empirical study of the passive takeover resistance of EOSIO, Steem and TRON. Our study identifies the diversity in voter preferences and characterizes the impact of this diversity on takeover resistance. Through both theoretical and empirical analyses, our study provides novel insights into the security of coin-based voting governance and suggests potential ways to improve the takeover resistance of any blockchain that implements this governance model. © 2023, CC BY-NC-ND.

关键词： Blockchain

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Protected Framework Employing Flexible and Optimum Arrangement in Cloud Computing

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Transactions on Emerging Telecommunications Technologies 2025年第6期36卷

作者： S. Shahul Hammed S. Pavalarajan C. Preethi K. Haripriya Department of Computer Science and Business Systems PSNA College of Engineering & Technology Dindigul India

The idea of cloud computing (CC) originates from making resources available for task execution. Cloud computing is an advancement of supercomputing. The main challenges in CC are the varying resources and workloads, leading to the need for efficient tasking and scheduling. Distributed task scheduling can help us better understand workflow scheduling; autonomous task scheduling that accounts for security and execution time, mutual trust among system participants, better energy efficacy, and system utilization, among other aspects. The MBABE technique expanded as multi-level blockchain attribute-based encryption, which is used to ensure data security. ABE is a combined encryption method that can be effectively utilized for security and access control. Additionally, a new algorithm is presented, which is optimized with a convolutional neural network and snoop slingshot spider optimization (CNN-S3SO). The cost functions are minimized using this S3SO for multipleusers in multiple cloud tasks computing progress. The technique relies on the actions of the arachnid in capturing targets and is utilized to arrange tasks for optimal throughput and minimal makespan. It is additionally recommended as a means of achieving convergence in a brief time frame. In addition, a protocol reliant on blockchain technology is utilized to encode data, ensuring secure transmission. Ultimately, the method is tested through a cloudlet simulator, and its efficiency is assessed through the analysis of the results. The outcome of the resource utilization rate is around 98%. It demonstrates that this methodology outperforms other task scheduling methods.

关键词： ABE blockchain cloud computing optimizer security snoop data task schedule

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Secure $k$k-NN Query on Encrypted Cloud Data with Multiple Keys

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IEEE Transactions on Big Data 2021年第4期7卷 689-702页

作者： Ke Cheng Liangmin Wang Yulong Shen Hua Wang Yongzhi Wang Xiaohong Jiang Hong Zhong School of Computer Science and Technology Xidian University Xi’an Shaanxi China School of Computer Science and Technology Anhui University Hefei Anhui China Centre of Applied Informatics College of Engineering and Science Victoria University VIC Australia Department of Computer Science Taiyuan Normal University Jinzhong China School of Systems Information Science Future University Hakodate Hakodate Hokkaido Japan School of Computer Science and Technology Xidian University Xi‘an Shaanxi China

The k-nearest neighbors (k-NN) query is a fundamental primitive in spatial and multimedia databases. It has extensive applications in location-based services, classification & clustering and so on. With the promise of confidentiality and privacy, massive data are increasingly outsourced to cloud in the encrypted form for enjoying the advantages of cloud computing (e.g., reduce storage and query processing costs). Recently, many schemes have been proposed to support k-NN query on encrypted cloud data. However, prior works have all assumed that the query users (QUs) are fully-trusted and know the key of the data owner (DO), which is used to encrypt and decrypt outsourced data. The assumptions are unrealistic in many situations, since many users are neither trusted nor knowing the key. In this paper, we propose a novel scheme for secure k-NN query on encrypted cloud data with multiple keys, in which the DO and each QU all hold their own different keys, and do not share them with each other; meanwhile, the DO encrypts and decrypts outsourced data using the key of his own. Our scheme is constructed by a distributed two trapdoors public-key cryptosystem (DT-PKC) and a set of protocols of secure two-party computation, which not only preserves the data confidentiality and query privacy but also supports the offline data owner. Our extensive theoretical and experimental evaluations demonstrate the effectiveness of our scheme in terms of security and performance.

关键词： Cloud computing Protocols computer science Encryption Servers Distributed databases

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Collaboration with Conversational AI Assistants for UX Evaluation: Questions and How to Ask them (Voice vs. Text)

arXiv

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arXiv 2023年

作者： Kuang, Emily Soure, Ehsan Jahangirzadeh Fan, Mingming Zhao, Jian Shinohara, Kristen Golisano College of Computing and Information Sciences Rochester Institute of Technology United States School of Computer Science University of Waterloo Canada Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology China School of Information Rochester Institute of Technology United States

AI is promising in assisting UX evaluators with analyzing usability tests, but its judgments are typically presented as non-interactive visualizations. Evaluators may have questions about test recordings, but have no way of asking them. Interactive conversational assistants provide a Q&A dynamic that may improve analysis efficiency and evaluator autonomy. To understand the full range of analysis-related questions, we conducted a Wizard-of-Oz design probe study with 20 participants who interacted with simulated AI assistants via text or voice. We found that participants asked for five categories of information: user actions, user mental model, help from the AI assistant, product and task information, and user demographics. Those who used the text assistant asked more questions, but the question lengths were similar. The text assistant was perceived as significantly more efficient, but both were rated equally in satisfaction and trust. We also provide design considerations for future conversational AI assistants for UX evaluation. © 2023, CC BY-NC-ND.

关键词： Visualization

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Diagnosis of COVID-19 Pneumonia via a Novel Deep Learning Architecture

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Journal of computer science & Technology 2022年第2期37卷 330-343页

作者： Xin Zhang Siyuan Lu Shui-Hua Wang Xiang Yu Su-Jing Wang Lun Yao Yi Pan Yu-Dong Zhang Department of Medical Imaging The Fourth People's Hospital of Huai'anHuai'an 223002China School of Informatics University of LeicesterLeicesterLE17RHU.K. School of Architecture Building and Civil Engineering Loughborough UniversityLoughboroughLE113TUU.K. School of Mathematics and Actuarial Science University of LeicesterLeicesterLE17RHU.K. Key Laboratory of Behavior Sciences Institute of PsychologyChinese Academy of SciencesBeijing 100101China Department of Psychology University of the Chinese Academy of SciencesBeijing 100101China Department of Infection Diseases The Fourth People's Hospital of Huai'anHuaian 223002China Department of Computer Science Georgia State UniversityAtlanta 30302-5060U.S.A. Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz University Jeddah 21589Saudi Arabia

COVID-19 is a contagious infection that has severe effects on the global economy and our daily *** diagnosis of COVID-19 is of importance for consultants,patients,and *** this study,we use the deep learning network AlexNet as the backbone,and enhance it with the following two aspects:1)adding batch normalization to help accelerate the training,reducing the internal covariance shift;2)replacing the fully connected layer in AlexNet with three classifiers:SNN,ELM,and ***,we have three novel models from the deep COVID network(DC-Net)framework,which are named DC-Net-S,DC-Net-E,and DC-Net-R,*** comparison,we find the proposed DC-Net-R achieves an average accuracy of 90.91%on a private dataset(available upon email request)comprising of 296 images while the specificity reaches 96.13%,and has the best performance among all three proposed *** addition,we show that our DC-Net-R also performs much better than other existing algorithms in the literature.

关键词： pneumonia COVID-19 convolutional neural network AlexNet deep learning

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Design and Development of a Non-Invasive Glucose Monitoring Device Using Advanced Microcontroller

Design and Development of a Non-Invasive Glucose Monitoring ...

引用

Expert Clouds and Applications (ICOECA), International Conference on

作者： S. Divya P Karthikeyan M. Vaigundamoorthi D Ramya Manzoore Elahi M. Soudagar Rajendiran M Department of Biomedical Engineering Dr. N.G.P. Institute of Technology Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Velammal College of Engineering and Technology Madurai Tamil Nadu India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Tamil Nadu India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Techinical Sciences Chennai Tamil Nadu India Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

Millions of individuals all over the world are living with diabetes, a chronic condition that necessitates regular monitoring of Blood Glucose Levels (BGL). The present technique for minimal invasive BGL monitoring involves taking a small blood sample and transferring it to a glucometer. However, this procedure can be uncomfortable for the patient. This research presents a method for non-invasively monitoring BGL with the help of a powerful controller called the ARM Cortex-M4. For non-invasive applications, we use photoplethysmography (PPG) signals. Using a photodiode and an infrared LED light, PPG samples are received from a finger sensor. Signal processing and feature extraction are carried out using the Gray-Level Co-occurrence Matrix (GLCM) method. To predict the BGL, two ML models are developed: one employing a Linear Regression (LR) model and the other an Artificial Neural Network (ANN) model. The experimental findings show that the ANN model is quite effective, with an R2 score of 0.986. After careful consideration, the ARM Cortex-M4 microcontroller's processing capabilities were found to be optimal for running the ANN model. The model must be fine-tuned before deployment so it can communicate with the microcontroller and provide correct inference in real time. The finger sensor simplifies PPG sample collection, and the OLED display makes it simple to view BGL.

关键词： Strips Microcontrollers Artificial neural networks Predictive models Organic light emitting diodes Signal processing Glucose

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Scalable Electrophysiology of Millimeter-Scale Animals with Electrode Devices

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Biomedical Engineering Frontiers 2023年第1期4卷 3-20页

作者： Kairu Dong Wen-Che Liu Yuyan Su Yidan Lyu Hao Huang Nenggan Zheng John A.Rogers Kewang Nan College of Pharmaceutical Sciences Zhejiang UniversityHangzhou 310058China National Key Laboratory of Advanced Drug Delivery and Release Systems Zhejiang UniversityHangzhou 310058China College of Biomedical Engineering&Instrument Science Zhejiang UniversityHangzhou310027China Department of Gastroenterology Brigham and Women’s HospitalHarvard Medical SchoolBostonMA 02115USA College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310058China Qiushi Academy for Advanced Studies Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China State Key Lab of Brain-Machine Intelligence Zhejiang UniversityHangzhou 310058China CCAI by MOE and Zhejiang Provincial Government(ZJU) Hangzhou 310027China Querrey Simpson Institute for Bioelectronics Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Department of Materials Science and Engineering Northwestern UniversityEvanstonIL 60208USA Department of Mechanical Engineering Northwestern UniversityEvanstonIL 60208USA Jinhua Institute of Zhejiang University Jinhua 321299China

Millimeter-scale animals such as Caenorhabditis elegans,Drosophila larvae,zebrafish,and bees serve as powerful model organisms in the fields of neurobiology and *** methods exist for recording large-scale electrophysiological signals from these *** approaches often lack,however,real-time,uninterrupted investigations due to their rigid constructs,geometric constraints,and mechanical mismatch in integration with soft *** recent research establishes the foundations for 3-dimensional flexible bioelectronic interfaces that incorporate microfabricated components and nanoelectronic function with adjustable mechanical properties and multidimensional variability,offering unique capabilities for chronic,stable interrogation and stimulation of millimeter-scale animals and miniature tissue *** review summarizes the most advanced technologies for electrophysiological studies,based on methods of 3-dimensional flexible bioelectronics.A concluding section addresses the challenges of these devices in achieving freestanding,robust,and multifunctional biointerfaces.

关键词： offering recording millimeter

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OCTAPUS: Empowering Next Generation Central Offices with Cross-Layer Network Intelligence Towards a Reconfigurable Data Plane 13th

OCTAPUS: Empowering Next Generation Central Offices with Cro...

引用

13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 International Workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

作者： Gatzianas, M. Kalfas, G. Vagionas, C. Vargemidou, M. Papadakis, A. Saliou, F. Theodoropoulou, E. Lyberopoulos, G. Piscione, P. Abdulwahed, A. Giardina, P. Gavrilut, V. Alsted, C. Gardes, F. Zeimpekis, I. Domínguez, T. Yu, X. Chakraborty, I. Atwi, H. Dris, S. Argyris, N. Bakopoulos, P. Petridou, S. Miliou, A. Pleros, N. Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece Center for Interdisciplinary Research and Innovation Thessaloniki Greece Department of Applied Informatics University of Macedonia Thessaloniki Greece Orange 2 Avenue Pierre Marzin Lannion22307 France Athens Greece Nextworks Srl Via Livornese 1027 Pisa56122 Italy Comcores ApS Haldor Topsøes Allé 1 Lyngby Denmark Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Teem Photonics Meylan France NVIDIA Photonic Systems Lab Ermou 56 Athens10563 Greece

ISBN: (纸本)9783031632266

Considering the challenges faced by the current Central Offices, this paper presents a novel architecture and related technological aspects of the Next Generation Central Offices (NGCOs), as envisioned within the OCTAPUS research project, towards the flexible support of the emerging capacity and latency demanding services. First, the main functional blocks of the OCTAPUS NGCO Data and Control planes are presented, with emphasis on the dynamicity of the optical paths within the NGCO and its reconfiguration capabilities. Then, focusing on the Control plane, we describe in detail its hierarchical structure, the role of the associated entities and the interactions among them. An example of network provisioning to support multiple concurrent next-generation services of realistic use cases in a real urban area is used to stress the need for NGCOs to adapt to different service requirements and temporal fluctuations in traffic demands, while catering for time-sensitive services with stringent delay requirements. © IFIP International Federation for Information Processing 2024.

关键词： Next generation networks

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Prove You Owned Me: One Step beyond RFID Tag/Mutual Authentication

arXiv

引用

arXiv 2022年

作者： Cai, Shaoying Li, Yingjiu Ma, Changshe Chow, Sherman S.M. Deng, Robert H. The College of Computer Science and Electronic Engineering Hunan University China The Computer and Information Science Department University of Oregon United States The School of Computer South China Normal University China The Department of Information Engineering The Chinese University of Hong Kong Hong Kong The School of Computing and Information Systems Singapore Management University Singapore

Radio Frequency Identification (RFID) is a key technology used in many applications. In the past decades, plenty of secure and privacy-preserving RFID tag/mutual authentication protocols as well as formal frameworks for evaluating them have been proposed. However, we notice that a property, namely proof of possession (PoP), has not been rigorously studied till now, despite it has significant value in many RFID applications. For example, in RFID-enabled supply chains, PoP helps prevent dishonest parties from publishing information about products/tags that they actually have never processed. We propose the first formal framework for RFID tag/mutual authentication with PoP after correcting deficiencies of some existing RFID formal frameworks. Our framework is based on a new privacy notion-unp#-privacy, and a new security notion-PoP credential unforgeability. We provide a generic construction to transform an RFID tag/mutual authentication protocol to one that supports PoP using a cryptographic hash function, a pseudorandom function (PRF) and a signature scheme. We prove that the constructed protocol is secure and privacy-preserving under our framework if all the building blocks possess desired security properties. Finally, we show an RFID mutual authentication protocol with PoP. Arming tag/mutual authentication protocols with PoP is an important step to strengthen RFID-enabled systems as it bridges the security gap between physical layer and data layer, and reduces the misuses of RFID-related data. Copyright © 2022, The Authors. All rights reserved.

关键词： Supply chains

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Automated detection of vertebral fractures from X-ray images: A novel machine learning model and survey of the field

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Neurocomputing 2024年 566卷

作者： Cheng, Li-Wei Chou, Hsin-Hung Cai, Yu-Xuan Huang, Kuo-Yuan Hsieh, Chin-Chiang Chu, Po-Lun Cheng, I-Szu Hsieh, Sun-Yuan Institute of Medical Informatics National Cheng Kung University No. 1 University Road Tainan70101 Taiwan Department of Computer Science and Information Engineering National Chi Nan University No. 1 University Rd. Puli Township Nantou54561 Taiwan Department of Computer Science and Information Engineering National Cheng Kung University No. 1 University Road Tainan70101 Taiwan Department of Orthopedics National Cheng Kung University Hospital College of Medicine National Cheng Kung University No. 138 Sheng Li Road Tainan701 Taiwan Department of Radiology Tainan Hospital Ministry of Health and Welfare No. 125 Jhongshan Rd. West Central Dist. Tainan70043 Taiwan College of Medicine National Cheng Kung University No. 1 University Road Tainan70101 Taiwan Department of Computer Science and Information Engineering Institute of Medical Information Institute of Manufacturing Information and Systems National Cheng Kung University. No. 1 University Road Tainan70101 Taiwan

Vertebral fractures are a common problem and the most prevalent of thoracolumbar compression and burst fractures. However, vertebral fractures are difficult to diagnose: an experienced orthopedist or radiologist is required to detect and determine the type of vertebral fracture. Thus, artificial intelligence methods for diagnosing vertebral fractures are clinically useful. On the basis of a review of 12 studies in the literature, the earliest of which was published in 2020, we propose a machine learning model that detects and determines the type of vertebral fracture on the basis of X-ray data. In this method, YOLOv4 and ResUNet are used to segment vertebral bodies from X-ray images. In evaluation experiments, our method had a precision of 99%, 74%, and 94% in identifying healthy vertebrae, compression fractures, and burst fractures, respectively. © 2023 Elsevier B.V.

关键词： Diagnosis

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