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A linkable signature scheme supporting batch verification for privacy protection in crowd-sensing

Digital Communications and Networks 2024年第3期10卷 645-654页

作者： Xu Li Gwanggil Jeon Wenshuo Wang Jindong Zhao School of Computer and Control Engineering Yantai UniversityYantai264005China Department of Embedded Systems Engineering Incheon National UniversityAcademyro-119Incheon22012Republic of Korea

The maturity of 5G technology has enabled crowd-sensing services to collect multimedia data over wireless network,so it has promoted the applications of crowd-sensing services in different fields,but also brings more privacy security challenges,the most commom which is privacy *** a privacy protection technology combining data integrity check and identity anonymity,ring signature is widely used in the field of privacy ***,introducing signature technology leads to additional signature verification *** the scenario of crowd-sensing,the existing signature schemes have low efficiency in multi-signature ***,it is necessary to design an efficient multi-signature verification scheme while ensuring *** this paper,a batch-verifiable signature scheme is proposed based on the crowd-sensing background,which supports the sensing platform to verify the uploaded multiple signature data efficiently,so as to overcoming the defects of the traditional signature scheme in multi-signature *** our proposal,a method for linking homologous data was presented,which was valuable for incentive mechanism and data *** results showed that the proposed scheme has good performance in terms of security and efficiency in crowd-sensing applications with a large number of users and data.

关键词： 5G network Crowd-sensing Privacy protection Ring signature Batch verification

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A Survey on Supervised,Unsupervised,and Semi-Supervised Approaches in Crowd Counting

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computers, Materials & Continua 2024年第12期81卷 3561-3582页

作者： Jianyong Wang Mingliang Gao Qilei Li Hyunbum Kim Gwanggil Jeon School of Electrical and Electronic Engineering Shandong University of TechnologyZibo255000China School of Electronic Engineering and Computer Science Queen Mary University of LondonLondonE14NSUK Department of Embedded Systems Engineering Incheon National UniversityIncheon22012Republic of Korea

Quantifying the number of individuals in images or videos to estimate crowd density is a challenging yet crucial task with significant implications for fields such as urban planning and public *** counting has attracted considerable attention in the field of computer vision,leading to the development of numerous advanced models and *** approaches vary in terms of supervision techniques,network architectures,and model ***,most crowd counting methods rely on fully supervised learning,which has proven to be ***,this approach presents challenges in real-world scenarios,where labeled data and ground-truth annotations are often *** a result,there is an increasing need to explore unsupervised and semi-supervised methods to effectively address crowd counting tasks in practical *** paper offers a comprehensive review of crowd counting models,with a particular focus on semi-supervised and unsupervised approaches based on their supervision *** summarize and critically analyze the key methods in these two categories,highlighting their strengths and ***,we provide a comparative analysis of prominent crowd counting methods using widely adopted benchmark *** believe that this survey will offer valuable insights and guide future advancements in crowd counting technology.

关键词： Crowd counting density estimation convolutional neural network(CNN) un/semi-supervised learning

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STM32 miner : A lightweight blockchain mining system 1

STM32 miner : A lightweight blockchain mining system

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1st IEEE International Conference on Design, Test and Technology of Integrated systems, DTTIS 2023

作者： Ktari, Jalel Choura, Hedi Frikha, Tarek Baklouti, Mouna Mejdi, Dhia Kotti, Molka Zribi, Ahmed Touil, Hassine Oueslati, Ghaith National Engineering School of Sfax Computer Embedded Systems Lab Sfax Tunisia National Engineering School of Sfax Data Engineering and Semantics Unit Sfax Tunisia National Engineering School of Sfax Computer Sciences and Applied Mathematiques Departement Sfax Tunisia

ISBN: (纸本)9798350316957

Despite being a promising area of exploration, the application of embedded systems in blockchain technology, particularly with FFGA or Raspberry technology, remains relatively limited. Despite the advantages offered by FPGAs, such as high-speed memory, parallel computing blocks, and a flexible architecture, their use in blockchain has primarily been focused on Proof of Work (PoW) consensus *** this paper, our goal is to address this gap by presenting the implementation of a blockchain application specifically tailored for the STM32 platform. By leveraging the capabilities of the STM32 microcontroller, we aim to demonstrate the practicality and effectiveness of embedded systems in blockchain technology, overcoming the limitations observed with previous platforms. © 2023 IEEE.

关键词： Blockchain

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Multi-layer composite autoencoders for semi-supervised change detection in heterogeneous remote sensing images

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Science China(Information Sciences) 2023年第4期66卷 124-125页

作者： Jiao SHI Tiancheng WU Hanwen YU A.K.QIN Gwanggil JEON Yu LEI School of Electronics and Information Northwestern Polytechnical University School of Resources and Environment University of Electronic Science and Technology of China Department of Computer Science and Software Engineering Swinburne University of Technology Department of Embedded Systems Engineering Incheon National University

With the increasing complexity of application scenarios, the fusion of different remote sensing data types has gradually become a trend, which can greatly improve the utilization of massive remote sensing *** the problem of change detection for heterogeneous remote images can be much more complicated than the traditional change detection for homologous remote sensing images,

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Deep learning based water leakage detection for shield tunnel lining

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Frontiers of Structural and Civil engineering 2024年第6期18卷 887-898页

作者： Shichang LIU Xu XU Gwanggil JEON Junxin CHEN Ben-Guo HE College of Computer Science Sichuan UniversityChengdu 610065China School of Computer Science and Engineering Northeastern UniversityShenyang 110004China Department of Embedded Systems Engineering Incheon National UniversityIncheon 22012Korea School of Software Dalian University of TechnologyDalian 116621China Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines Northeastern UniversityShenyang 110819China

Shield tunnel lining is prone to water leakage,which may further bring about corrosion and structural damage to the walls,potentially leading to dangerous *** avoid tedious and inefficient manual inspection,many projects use artificial intelligence(Al)to detect cracks and water leakage.A novel method for water leakage inspection in shield tunnel lining that utilizes deep learning is introduced in this *** proposal includes a ConvNeXt-S backbone,deconvolutional-feature pyramid network(D-FPN),spatial attention module(SPAM).and a detection *** can extract representative features of leaking areas to aid inspection *** further improve the model's robustness,we innovatively use an inversed low-light enhancement method to convert normally illuminated images to low light ones and introduce them into the training *** experiments are performed,achieving the average precision(AP)score of 56.8%,which outperforms previous work by a margin of 5.7%.Visualization illustrations also support our method's practical effectiveness.

关键词： water leakage detection deep learning deconvolutional-feature pyramid spatial attention

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Combining Automatic Annotation with Human Validation for the Semantic Enrichment of Cultural Heritage Metadata

Combining Automatic Annotation with Human Validation for the...

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2024 Computational Humanities Research Conference, CHR 2024

作者： Kaldeli, Eirini Chortaras, Alexandros Lyberatos, Vassilis Liartis, Jason Kantarelis, Spyridon Stamou, Giorgos AI and Learning Systems Lab School of Electrical and Computer Engineering National Technical University of Athens Greece

The addition of controlled terms from linked open datasets and vocabularies to metadata can increase the discoverability and accessibility of digital collections. However, the task of semantic enrichment requires a lot of effort and resources that cultural heritage organizations often lack. State-of-the-art AI technologies can be employed to analyse textual metadata and match it with external semantic resources. Depending on the data characteristics and the objective of the enrichment, different approaches may need to be combined to achieve high-quality results. What is more, human inspection and validation of the automatic annotations should be an integral part of the overall enrichment methodology. In the current paper, we present a methodology and supporting digital platform, which combines a suite of automatic annotation tools with human validation for the enrichment of cultural heritage metadata within the European data space for cultural heritage. The methodology and platform have been applied and evaluated on a set of datasets on crafts heritage, leading to the publication of more than 133K enriched records to the Europeana platform. A statistical analysis of the achieved results is performed, which allows us to draw some interesting insights as to the appropriateness of annotation approaches in different contexts. The process also led to the creation of an openly available annotated dataset, which can be useful for the in-domain adaptation of ML-based enrichment tools. © 2024 Copyright for this paper by its authors.

关键词： Semantics

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Artificial Intelligence for securing SDIoT: Challenges and countermeasures 20

Artificial Intelligence for securing SDIoT: Challenges and c...

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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Zaidoun, Ameur Salem Baccouch, Hajer Guermazi, Abderrahmen Lachiri, Zied National Engineering School of Tunis Signal Images and Information Technologies Lab Tunisia Higher Institute of Technological Studies of Siliana Tunisia National Engineering School of Sfax Computer and Embedded Systems Lab Tunisia Higher Institute of Technological Studies of Sfax Tunisia

ISBN: (纸本)9798350332568

SDIoT (Software Defined IoT) is an emerging IoT technology, deployed using SDN architecture;nevertheless, it presents several weaknesses, which can be raised in different layers. To mitigate SDIoT intrusions and attacks, security as used in a common network cannot provide a complete solution and must be enhanced with AI (Artificial Intelligence) based countermeasures tools, mainly machine and deep learning. The paper identifies the salient features of SDIoT technology. Afterwards, it describes the most common attacks against SDIoT networks and possible countermeasures using several deep learning algorithms. In addition, the paper describes datasets used for learning steps. At the end, it discusses the suitability of AI based security tools to some attacks. © 2023 IEEE.

关键词： Deep learning

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Fuzz-classification(p,l)-Angel:An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches

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Digital Communications and Networks 2023年第5期9卷 1131-1140页

作者： Tehsin Kanwal Hasina Attaullah Adeel Anjum Abid Khan Gwanggil Jeon Department of Computer Science COMSATS University IslamabadPakistan Department of Information Technology Quaid-e-Azam University IslamabadPakistan College of Science and Engineering School of Computing and MathsUniversity of DerbyDE221GBUK Department of Embedded Systems Engineering Incheon National UniversitySouth Korea

The inability of traditional privacy-preserving models to protect multiple datasets based on sensitive attributes has prompted researchers to propose models such as SLOMS,SLAMSA,(p,k)-Angelization,and(p,l)-Angelization,but these were found to be insufficient in terms of robust privacy and performance.(p,l)-Angelization was successful against different privacy disclosures,but it was not *** the best of our knowledge,no robust privacy model based on fuzzy logic has been proposed to protect the privacy of sensitive attributes with multiple *** this paper,we suggest an improved version of(p,l)-Angelization based on a hybrid AI approach and privacy-preserving approach like ***-classification(p,l)-Angel uses artificial intelligence based fuzzy logic for classification,a high-dimensional segmentation technique for segmenting quasi-identifiers and multiple sensitive *** demonstrate the feasibility of the proposed solution by modelling and analyzing privacy violations using High-Level Petri *** results of the experiment demonstrate that the proposed approach produces better results in terms of efficiency and utility.

关键词： Generalization Fuzzy-logic MSA Privacy disclosures Membership function (p,l)-Angelization QT HLPN

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Accurate and Approximate Solutions of Nonlinear Electron Plasma Oscillations

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International Journal of Applied and Computational Mathematics 2024年第4期10卷 1-24页

作者： Kontomaris, S.V. Malamou, A. Faculty of Engineering and Architecture Metropolitan College BioNanoTec LTD Radar Systems and Remote Sensing Lab of School of Electrical and Computer Engineering of National Technical University of Athens

Nonlinear oscillations can be used to describe a significant number of physical phenomena from classic to modern physics. Thus, it is important to find accurate solutions using elementary functions that can be easily applied in relative applications. In this paper, the oscillations described by the nonlinear differential equation u^′′=ω_p0²(1-u∓2β²u^γ), where ω_p0,β,γ are positive constants are being considered. The aforementioned differential equations are of great importance since they are used to describe electron plasma oscillations under the influence of temperature effects and for big oscillations amplitudes. The amplitude and period of the oscillation for different values of constants β,γ are derived using rigorous mathematical analysis and simplified approximate methods. In addition, accurate solutions u=f(t) in the form of elementary functions are also presented. The results of this paper can be also applied to similar cases in physics (e.g. classic mechanics) where differential equations of the same form apply. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Nonlinear differential equations Nonlinear oscillation’s period Plasma physics Thermal effects

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Towards Simpler Modelling Expressions for the Mechanical Characterization of Soft Materials

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Micro and Nanosystems 2024年第3期16卷 172-182页

作者： Kontomaris, Stylianos-Vasileios Malamou, Anna Stylianou, Andreas Chliveros, Georgios Faculty of Engineering and Architecture Metropolitan College Athens Greece BioNanoTec LTD Nicosia Cyprus Radar Systems and Remote Sensing Lab School of Electrical & Computer Engineering National Technical University of Athens Athens Greece Department of Mechanical Engineering Faculty of Engineering School of Sciences European University Cyprus Nicosia2404 Cyprus

Aims: The aim of this paper is to develop a new, simple equation for deep spherical indentations. Background: The Hertzian theory is the most widely applied mathematical tool when testing soft materials because it provides an elementary equation that can be used to fit force-indentation data and determine the mechanical properties of the sample (i.e., its Young’s modulus). However, the Hertz equation is only valid for parabolic or spherical indenters at low indentation depths. For large indentation depths, Sneddon’s extension of the Hertzian theory offers accurate force-indentation equations, while alternative approaches have also been developed. Despite ongoing mathematical efforts to derive new accurate equations for deep spherical indentations, the Hertz equation is still commonly used in most cases due to its simplicity in data processing. Objective: The main objective of this paper is to simplify the data processing for deep spherical indentations, primarily by providing an accurate equation that can be easily fitted to force-indentation data, similar to the Hertzian equation. Methods: A simple power-law equation is derived by considering the equal work done by the indenter using the actual equation. Results: The mentioned power-law equation was tested on simulated force-indentation data created using both spherical and sphero-conical indenters. Furthermore, it was applied to experimental force-indentation data obtained from agarose gels, demonstrating remarkable accuracy. Conclusion: A new elementary power-law equation for accurately determining Young’s modulus in deep spherical indentation has been derived. © 2024 Bentham Science Publishers.

关键词： Spheres

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