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A systematic literature review of blockchain cyber security

Digital Communications and Networks 2020年第2期6卷 147-156页

作者： Paul J.Taylor Tooska Dargahi Ali Dehghantanha Reza M.Parizi Kim-Kwang Raymond Choo School of Computing Science&EngineeringUniversity of SalfordManchesterUK Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Software Engineering and Game Development Kennesaw State UniversityMariettaGA30060USA Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Since the publication of Satoshi Nakamoto's white paper on Bitcoin in 2008,blockchain has(slowly)become one of the most frequently discussed methods for securing data storage and transfer through decentralized,trustless,peer-to-peer *** research identifies peer-reviewed literature that seeks to utilize blockchain for cyber security purposes and presents a systematic analysis of the most frequently adopted blockchain security *** findings show that the Internet of Things(IoT)lends itself well to novel blockchain applications,as do networks and machine visualization,public-key cryptography,web applications,certification schemes and the secure storage of Personally Identifiable Information(PII).This timely systematic review also sheds light on future directions of research,education and practices in the blockchain and cyber security space,such as security of blockchain in IoT,security of blockchain for AI data,and sidechain security.

关键词： Blockchain Smart contracts Cyber security Distributed ledger technology IoT Cryptocurrency Bitcoin

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An Optimized Approach to Hourly Temperature and Humidity Setpoint Generation for Reducing Tomato Disease and Saving Power Cost in Greenhouses

SSRN

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SSRN 2024年

作者： Sánchez-Molina, Jorge Antonio Wang, Hui Laktionov, Ivan Díaz, Francisco Rodríguez Li, Ming BIPP Institute of Plant Protection Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China Department of Computer Systems Software Dnipro University of Technology DniproUA49005 Ukraine Department of Informatics University of Almería ceiA3 CIESOL Almería04120 Spain Beijing Research Center for Information Technology in Agriculture National Engineering Research Centre for Information Technology in Agriculture National Engineering Laboratory for Agri-product Quality Traceability Key Laboratory of Agri-informatics Ministry of Agriculture Beijing100097 China

Grey leaf spot is a main leaf disease of tomato in Mediterranean greenhouses, characterized by warm temperatures and high humidity during the spring and winter seasons, hence suitable for pathogen infection and spore spread. Consequently, the utilization of automatic control and optimization algorithms has emerged as effective means to prevent chemical-oriented disease control and enhancing the overall quality and safety of food and crops. The aim of this work is to search an optimal strategy for precision management on greenhouse tomato growth environment. So, multi-objective optimization rises to an alternative to achieve this goal. While there were lots of research on determining trajectories to control a desired crop growth, and lacking works that optimize climate conditions for restraining the damage of disease on crop. Based on the multi-objective genetic algorithm optimization method (MOGA), the solution balances the conflict of two objectives: minimum power cost caused by climate control and maximum health leaves with few effects of grey leaf spot. This study also highlights disease and high temperature impact on tomato growth, which are as inequality constraints of the optimization problems. The results showed MOGA strategy performers good, the minimum power cost is only need 0.084€*day-1 in warm weather condition, as well as 3.74 €*day-1 in cold weather condition, the uninfected LAI (m2[Leaves](m-2[soils]*day-1)) is the range of [0.14 0.20]. The yearly power cost at least [308 1365]€.These are able to embed within a control scheme for achieving optimization purpose. The farmer receives the data necessary for decision-making to establish the setpoints during the crop cycle, modifying the control decisions, lowering production costs, reducing the use of pesticides and increasing the system efficiency to optimize crop growth. © 2024, The Authors. All rights reserved.

关键词： Crops

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Hardware Design and Security Needs Attention: From Survey to Path Forward

arXiv

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arXiv 2025年

作者： Ghimire, Sujan Chowdhury, Muhtasim Alam Latibari, Banafsheh Saber Mamun, Muntasir Carpenter, Jaeden Wolf Tan, Benjamin Pearce, Hammond Satam, Pratik Salehi, Soheil Systems and Industrial Engineering Department University of Arizona TucsonAZ United States Electrical and Computer Engineering Department University of Arizona TucsonAZ United States Department of Electrical and Software Engineering University of Calgary Alberta CalgaryAB Canada School of Computer Science and Engineering University of New South Wales Sydney Australia

Recent advances in attention-based artificial intelligence (AI) models have unlocked vast potential to automate digital hardware design while enhancing and strengthening security measures against various threats. This rapidly emerging field leverages Large Language Models (LLMs) to generate HDL code, identify vulnerabilities, and sometimes mitigate them. The state of the art in this design automation space utilizes optimized LLMs with HDL datasets, creating automated systems for register transfer level(RTL) generation, verification, and debugging and establishing LLM-driven design environments for streamlined logic designs. Additionally, attention-based models like graph attention have shown promise in chip design applications, including floorplanning. This survey investigates the integration of these models into hardware-related domains, emphasizing logic design and hardware security, with or without the use of IP libraries. This study explores the commercial and academic landscape, highlighting technical hurdles and future prospects for automating hardware design and security. Moreover, it provides new insights into the study of LLM-driven design systems, advances in hardware security mechanisms, and the impact of influential works on industry practices. Through the examination of 30 representative approaches and illustrative case studies, this paper underscores the transformative potential of attention-based models in revolutionizing hardware design while addressing the challenges that lie ahead in this interdisciplinary domain. © 2025, CC BY.

关键词： Hardware-software codesign

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Contemporary software Modernization: Strategies, Driving Forces, and Research Opportunities

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ACM Transactions on software engineering and Methodology 2025年第5期34卷

作者： Assunção, Wesley K.G. Marchezan, Luciano Arkoh, Lawrence Egyed, Alexander Ramler, Rudolf Department of Computer Science North Carolina State University RaleighNC United States Institute of Software Systems Engineering Johannes Kepler University Linz Linz Austria Software Competence Center Hagenberg GmbH Hagenberg Austria

software modernization is a common activity in software engineering, since technologies advance, requirements change, and business models evolve. Differently from conventional software evolution (e.g., adding new features, enhancing performance, or adapting to new requirements), software modernization involves re-engineering entire legacy systems (e.g., changing the technology stack, migrating to a new architecture style, or programming paradigms). Given the pervasive nature of software today, modernizing legacy systems is paramount to provide customers with competitive and innovative products and services, while keeping companies profitable. Despite the prevalent discussion of software modernization in gray literature, and the many papers in the literature, there is no work presenting a "big picture" of contemporary software modernization, describing challenges, and providing a well-defined research agenda. The goal of this work is to describe the state of the art in software modernization in the past 10 years. We collect the state of the art by performing a rapid review (searching five digital libraries), identifying potential 3,460 studies, leading to a final set of 126. We analyzed these studies to understand which strategies are employed, the driving forces that lead organizations to modernize their systems, and the challenges that need to be addressed. The results show that studies in the last 10 years have explored eight strategies for modernizing legacy systems, namely cloudification, architecture redesign, moving to a new programming language, targeting reuse optimization, software modernization for new hardware integration, practices to leverage automation, database modernization, and digital transformation. Modernization is triggered by 14 driving forces, with the most common ones being reducing operational costs, improving performance and scalability, and reducing complexity. In © 2025 Copyright held by the owner/author(s). Publication rights licensed to

关键词： Legacy systems

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Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges

arXiv

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arXiv 2023年

作者： Liu, Qi Yang, Zhiyun Ji, Ru Zhang, Yonghong Bilal, Muhammad Liu, Xiaodong Vimal, S. Xu, Xiaolong The Wuxi University 333 Xishan Avenue Wuxi214105 China The School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China The Division of Computer and Electronic Systems Engineering Hankuk University of Foreign Studies Korea Republic of The School of Computing Edinburgh Napier University EdinburghEH10 5DT United Kingdom The Department of Artificial Intelligence & DS Ramco Institute of Technology Tamilnadu India

Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this paper, recent relevant scientific investigation and practical efforts using Deep Learning (DL) models for weather radar data analysis and pattern recognition have been reviewed;particularly, in the fields of beam blockage correction, radar echo extrapolation, and precipitation nowcast. Compared to traditional approaches, present DL methods depict better performance and convenience but suffer from stability and generalization. In addition to recent achievements, the latest advancements and existing challenges are also presented and discussed in this paper, trying to lead to reasonable potentials and trends in this highly-concerned *** Codes I.2, I.4, I.5 © 2023, CC BY-NC-SA.

关键词： Extrapolation

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Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing

Multi-Relational Graph Neural Architecture Search with Fine-...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Xin Zheng Miao Zhang Chunyang Chen Chaojie Li Chuan Zhou Shirui Pan Department of Software Systems and Cybersecurity Monash University Australia School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) China School of Electrical Engineering and Telecommunications University of New South Wales Australia Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China School of Information and Communication Technology Griffith University Australia

Graph neural architecture search (NAS) has gained great popularity in automatically designing powerful graph neural networks (GNNs) with superior learning abilities, significantly relieving human effort and expertise reliance. Despite the advanced performance of automated learning, existing graph NAS models mainly work on single-relational graphs, while the widespread multi-relational graphs in real-world applications, are not well addressed. Moreover, current search spaces of automated GNNs are generally coarse-grained by simply integrating typical GNN layers and hyper-parameters, resulting in severe limitations on search capacities and scopes for creating innovative GNN architectures. To tackle the limitations of single-relational setting and coarse-grained search space design in existing graph NAS, in this paper, we propose a novel framework of multi-relational graph neural architecture search, dubbed MR-GNAS, to automatically develop innovative and excellent multi-relational GNN architectures. Specifically, to enlarge search capacities and improve search flexibility, MR-GNAS contains a fine-grained search space that embraces the full-pipe multi-relational message passing schema, enabling expressive architecture search scopes. With the well-designed fine-grained search space, MR-GNAS constructs a relation-aware supernet with a tree topology, to jointly learn discriminative node and relation representations. By searching with a gradient-based strategy in the supernet, the proposed MR-GNAS could derive excellent multi-relational GNN architectures in multi-relational graph analysis. Extensive experiments on entity classification and link prediction tasks over multi-relational graphs illustrate the effectiveness and superiority of the proposed method.

关键词： Message passing Graph neural networks Topology Data mining Task analysis

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Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment

arXiv

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arXiv 2024年

作者： Wu, Jiaqi Zhang, Shihao Chen, Simin Wang, Lixu Wang, Zehua Chen, Wei He, Fangyuan Tian, Zijian Yu, F. Richard Leung, Victor C.M. Beijing100083 China Department of Electrical and Computer Engineering University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada University of Texas at dallas 800 W Campbell Rd RichardsonTX75080 United States Northwestern University 633 Clark St EvanstonIL60208 United States School of Computer Science and Technology China University of Mining and Technology Jiangsu province Xuzhou221116 China Department of Electrical and Computer Engineering The University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China College of Computer Science and Software Engineering Shenzhen University Shenzhen528060 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada College of Applied Science and Technology Beijing Union University Beijing100012 China

Recently, edge computing has emerged as a prevailing paradigm in applying deep learning-based object detection models, offering a promising solution for time-sensitive tasks. However, existing edge object detection faces several challenges: 1) These methods struggle to balance detection precision and model lightweightness. 2) Existing generalized edge-deployment designs offer limited adaptability for object detection. 3) Current works lack real-world evaluation and validation. To address these challenges, we propose the Edge Detection Toolbox (ED-TOOLBOX), which leverages generalizable plug-and-play components to enable edge-site adaptation of object detection models. Specifically, we propose a lightweight Reparameterized Dynamic Convolutional Network (Rep-DConvNet) that employs a weighted multi-shape convolutional branch structure to enhance detection performance. Furthermore, ED-TOOLBOX includes a Sparse Cross-Attention (SC-A) network that adopts a localized-mapping-assisted self-attention mechanism to facilitate a well-crafted Joint Module in adaptively transferring features for further performance improvement. In real-world implementation and evaluation, we incorporate an Efficient Head into the popular You-Only-Look-Once (YOLO) approach to achieve faster edge model optimization. Moreover, we identify that helmet detection—one of the most representative edge object detection tasks—overlooks band fastening, which introduces potential safety hazards. To address this, we build a Helmet Band Detection Dataset (HBDD) and apply an edge object detection model optimized by the ED-TOOLBOX to tackle this real-world task. Extensive experiments validate the effectiveness of components in ED-TOOLBOX. In visual surveillance simulations, ED-TOOLBOX-assisted edge detection models outperform six state-of-the-art methods, enabling real-time and accurate detection. These results demonstrate that our approach offers a superior solution for edge object detection. Copyright © 2024, T

关键词： Deep learning

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Modeling and Simulation of Total Attenuation of P2P NLOS 5G and Beyond Wireless Communication systems Operating in FR2 Bands in Nigeria

Modeling and Simulation of Total Attenuation of P2P NLOS 5G ...

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Multidisciplinary engineering and Applied Science (ICMEAS), International Conference on

作者： Emmanuel Alozie Nasir Faruk Abubakar Abdulkarim Aliyu D. Usman Yusuf Olayinka Imam-Fulani Salisu Garba Kayode S. Adewole Abdulkarim A. Oloyede Olugbenga A. Sowande Bashir Abdullahi Baba Abdulwaheed Musa Agbotiname Lucky Imoize Yinusa A. Adediran Hawau I. Olagunju Lawan S. Taura Department of Information Technology Sule Lamido University Kafin Hausa Nigeria Directorate of Information and Communication Technology Sule Lamido University Kafin Hausa Nigeria Department of Electrical Engineering Ahmadu Bello University Nigeria Department of Electrical and Telecommunications Engineering Kampala International University Kansanga Kampala Uganda Department of Electronics and Telecommunication Engineering Ahmadu Bello University Nigeria Department of Telecommunication Science University of Ilorin Ilorin Nigeria Department of Software Engineering Sule Lamido University Kafin Hausa Nigeria Department of Computer Science University of Ilorin Ilorin Nigeria Department of Cyber Security Sule Lamido University Kafin Hausa Nigeria Department of Electrical and Computer Engineering Kwara State University Malete Nigeria Institute for Intelligent Systems University of Johannesburg Johannesburg South Africa Department of Electrical and Electronics Engineering University of Lagos Akoka Lagos Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum Germany Department of Electrical and Electronics Engineering University of Ilorin Ilorin Nigeria Department of Physics Sule Lamido University Kafin Hausa Nigeria

Signal propagation in a particular region differs from another due to differences in atmospheric, climatic and environmental properties, distinct terrain and clutter features. Adequate analysis is essential to understand the radio propagation behavior in a particular region. The ITU-R designated four rain regions, M, N, P, and Q, for Nigeria representing the rain rate distribution and also provided further classifications based on ground conductivity, among other salient parameters. Based on these classifications, this paper utilized the EDX Signal Pro software® to model and simulate a typical Point-to-Point (P2P), Non-Line of Sight (NLOS) link scenarios for 5G networks. The objective was to estimate and compare the total loss, excess loss, and flat fade margins for each rain region in Nigeria. Results obtained from the comparison showed that signals propagating in region N experience the highest level of losses and fading, while, region Q has the least losses and fading.

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Signal Attenuation Modeling and Simulation for 5G and Beyond P2P Wireless Communication Networks in FR2 Bands: Comparison within M-Region in Nigeria

Signal Attenuation Modeling and Simulation for 5G and Beyond...

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Multidisciplinary engineering and Applied Science (ICMEAS), International Conference on

作者： Emmanuel Alozie Nasir Faruk Abubakar Abdulkarim Aliyu D. Usman Yusuf Olayinka Imam-Fulani Salisu Garba Kayode S. Adewole Abdulkarim A. Oloyede Olugbenga A. Sowande Bashir Abdullahi Baba Abdulwaheed Musa Agbotiname Lucky Imoize Yinusa A. Adediran Hawau I. Olagunju Lawan S. Taura Department of Information Technology Sule Lamido University Kafin Hausa Nigeria Directorate of Information and Communication Technology Sule Lamido University Kafin Hausa Nigeria Department of Electrical Engineering Ahmadu Bello University Kafin Hausa Nigeria Department of Electrical and Telecommunications Engineering Kampala International University Kampala Uganda Department of Electronics and Telecommunication Engineering Ahmadu Bello University Zaria Nigeria Department of Telecommunication Science University of Ilorin Ilorin Nigeria Department of Software Engineering Sule Lamido University Kafin Hausa Nigeria Department of Computer Science University of Ilorin Ilorin Nigeria Department of Cyber Security Sule Lamido University Kafin Hausa Nigeria Department of Electrical and Computer Engineering Kwara State University Malete Nigeria Institute for Intelligent Systems University of Johannesburg Johannesburg South Africa Department of Electrical and Electronics Engineering University of Lagos Lagos Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum Germany Department of Electrical and Electronics Engineering University of Ilorin Ilorin Nigeria Department of Physics Sule Lamido University Kafin Hausa Nigeria

ITU-R categorized Nigeria into four rain regions (i.e., M, N, P, and Q) depending on the atmospheric conditions. Previous works that have conducted rain and attenuation modeling and simulations have assumed similar signal propagation behavior and parameters within locations categorized under the same region. This paper aims to explore these assumptions by conducting an extensive radio propagation simulations of point-to-point microwave links with a clear line-of-sight in order to estimate the total path loss (attenuation), excess path loss, and flat fade margins for each of the locations within the M-regions, i.e., Kano, Sokoto, and Adamawa. Results obtained showed that in all the locations, the loss monotonically increases with distance, with Sokoto having the highest level of signal losses and fading, while, Adamawa has the lowest. The deviation for both total loss, excess loss, and flat fading margin was found to be between 15 dB across the region.

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Generation and search for the shortest path in two-dimensional labyrinths as a model for optimizing routing processes in the packet switching network 4

Generation and search for the shortest path in two-dimension...

引用

4th International Conference on Future Networks and Distributed systems, ICFNDS 2020

作者： Dagaev, Alexander Borodyansky, Yuriy Pomogalova, Albina Department of Software Engineering and Computer Science The Bonch-Bruevich State University of Telecommunications St. Petersburg Russia Department of Protected Information Systems The Bonch-Bruevich State University of Telecommunications St. Petersburg Russia

ISBN: (纸本)9781450388863

The algorithms for generating and finding the shortest path in two-dimensional labyrinths and their characteristics are considered. The aim of the study is to determine the dependence of the working time of the shortest path search algorithms on the characteristics of mazes. This may allow these algorithms to be used to optimise routing processes in packet switching networks. All of the characteristics of the algorithms under consideration are described in detail. These search algorithms also allow for paralleling, so they can be used when creating games or any special applications. Such generation algorithms have been selected, the resulting mazes of which have different characteristics, thus making it possible to determine the required dependence. The peculiarity of applying the result of this research is that the fastest search algorithm can be selected for the generation algorithm or for specific characteristics of an already generated maze. The search algorithms can be improved to find paths in mazes in N-dimensional spaces. This search extension possibility can be widely used not only for working with mazes, but also with any other structure of a given coordinate system. © 2020 ACM.

关键词： Packet switching

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