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Review of threats and existing algorithmic solutions for securing WSNs 17

Review of threats and existing algorithmic solutions for sec...

引用

17th ieee international Scientific conference on informatics, informatics 2024

作者： Janovec, Michal Papan, Jozef Hraska, Michal University of Žilina Faculty of Management Science and Informatics Slovakia

ISBN: (纸本)9798350387674

Wireless sensor networks (WSNs) are one of the main parts of the IoT world. WSNs are widely used in various fields, such as medical monitoring, industrial automation, environmental monitoring, and home automation. As the use of WSNs increases, many problems need to be solved. One of the most dangerous issues is security. Security is critical as sensitive data and control signals may be present in the transmission. However, the solution to this problem is very demanding regarding computing power and transmission capacity. In this article, we will describe the individual threats in WSNs and the various solutions many researchers have investigated to counter these threats as effectively as possible. © 2024 ieee.

关键词： Wireless sensor networks

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computing the Laser Radar Cross Section of the Typical Object 2

Computing the Laser Radar Cross Section of the Typical Objec...

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2nd international conference on Mechatronics, IoT and Industrial informatics, ICMIII 2024

作者： Wang, Yun Dong, Liang Wu, Jianwei Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9798350386639

The research on computing laser radar cross sections (LRCS) is of great significance for national defense, aviation, aerospace, meteorology and other scenes. In this paper, a computing model for LRCS was created, and a computing software for LRCS was designed based on "Graphical Electromagnetic computing"(GRECO) and OpenGL. The full-radiation LRCS of the object model was analyzed, and the mono-static full-radiation LRCSs of Teflon sphere and the object model under different surface materials were computed and studied on the software. © 2024 ieee.

关键词： Radar cross section

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An Evolutionary Algorithm for Adversarial SQL Injection Attack Generation 20

An Evolutionary Algorithm for Adversarial SQL Injection Atta...

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20th ieee international conference on Intelligence and Security informatics, ISI 2023

作者： Issakhani, Maryam Huang, Mufeng Tayebi, Mohammad A. Lashkari, Arash Habibi School of Information Technology York University Toronto Canada School of Computing Science Simon Fraser University Burnaby Canada

ISBN: (纸本)9798350337730

Web application security poses ongoing challenges for organizations, and researchers have increasingly turned to machine and deep learning techniques to address vulnerabilities such as SQL injection and Cross Site Scripting. While these studies have made notable progress, the vulnerability to adversarial attacks remains a significant challenge. In this work, we aim to explore the impact of adversarial examples on machine and deep learning applications for detecting web vulnerabilities. We propose an evolutionary algorithm to create effective adversarial samples for bypassing various detection systems by iterative exploration of the search space. The effectiveness of our proposed approach is validated through rigorous testing on different diverse SQL injection detection systems. © 2023 ieee.

关键词： Evolutionary algorithms

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Deep Reinforcement Learning for Energy-Efficient Task Offloading in Cooperative Vehicular Edge Networks 21

Deep Reinforcement Learning for Energy-Efficient Task Offloa...

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ieee 21st international conference on Industrial informatics (INDIN)

作者： Agbaje, Paul Nwafor, Ebelechukwu Olufowobi, Habeeb Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA Villanova Univ Dept Comp Sci Villanova PA USA

ISBN: (纸本)9781665493130

In the Internet of Vehicle ecosystem, multi-access edge computing (MEC) enables mobile nodes to improve their communication and computation capabilities by executing transactions in near real-time. However, the limited energy and computation capabilities of MEC servers limit the efficiency of task computation. Moreover, the use of static edge servers in dense vehicular networks may lead to an influx of service requests that negatively impact the quality of service (QoS) of the edge network. To enhance the QoS and optimize network resources, minimizing offloading computation costs in terms of reduced latency and energy consumption is crucial. In this paper, we propose a cooperative offloading scheme for vehicular nodes, using vehicles as mobile edge servers, which minimizes energy consumption and network delay. In addition, an optimization problem is presented, which is formulated as a Markov Decision Process (MDP). The solution proposed is a deep reinforcement-based Twin Delayed Deep Deterministic policy gradient (TD3), ensuring an optimal balance between task computation time delay and the energy consumption of the system.

关键词： Smart cities vehicular edge computing Internet of vehicles deep reinforcement learning task offloading TD3

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OpenCyberCity Testbed's Recent progress in Smart City Management 10

OpenCyberCity Testbed's Recent Progress in Smart City Manage...

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international conference on Smart computing (SMARTCOMP)

作者： Zaman, Mostafa Malik, Ahmed Al Islam, Maher Van, Courtney Pollard, Alyssa Davis, Brittany Zohrabi, Nasibeh Abdelwahed, Sherif Virginia Commonwealth Univ Dept Elect & Comp Engn Richmond VA 23284 USA Virginia Commonwealth Univ Dept Comp Sci Richmond VA USA Virginia State Univ Dept Comp Sci Petersburg VA USA Penn State Univ Dept Engn Media PA USA

ISBN: (纸本)9798350349955;9798350349948

Smart cities have appeared as an essential paradigm, leveraging advanced technology and data-driven techniques to enhance residents' quality of life, drive economic growth, improve governance, and facilitate environmental sustainability. Promoting experimental testing of existing and emerging technologies in realistic smart-city-simulated environments is paramount for their development. OpenCyberCity, a smart city testbed developed at Virginia Commonwealth University, echoes this progress by incorporating smart functionalities such as smart buildings, traffic systems, manufacturing, data analytics, autonomous response systems, and microgrid infrastructure capabilities. This paper presents recent expansions and updates on the OpenCyberCity testbed, enabling further experimentation across various smart city domains, with the aim of improving energy conservation, transportation, building management, resilience, and sustainable infrastructure development.

关键词： Smart City Smart Grid Smart Manufacturing System Smart Street and Traffic Light System Data Analytics

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A microservices-based architecture for data and software management of heavy equipment digital twins 21

A microservices-based architecture for data and software man...

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ieee 21st international conference on Industrial informatics (INDIN)

作者： Zhidchenko, Victor Startcev, Egor Kortelainen, Juha Zeb, Akhtar Torvikoski, Leo Torkabadi, Saeid Handroos, Heikki LUT Univ Dept Mech Engn Lappeenranta Finland VTT Tech Res Ctr Finland Knowledge driven Design Res Unit Espoo Finland Eurostep Oy Espoo Finland Eurostep AB Gothenburg Sweden

ISBN: (纸本)9781665493130

Digital twins improve the performance of heavy equipment and decrease its operational costs. To be effective, they must run along decades of a real machine lifecycle. Ensuring coherence between a real machine and its digital twin over such a long period is a challenging task that has not yet been well-studied. This task involves preserving the design and operational data and periodic execution of digital twin software that processes such data. The circumstances of heavy equipment operation complicate the task. This paper considers the problem of digital twin data and software management in light of the unique challenges related to heavy equipment. It presents an experimental case study for running digital twins of mobile log cranes using a data model and a microservices-based architecture developed by the authors. The results demonstrate the capability of the architecture for running physics-based digital twins of heavy equipment in a heterogeneous execution environment consisting of local, edge, and cloud computing resources.

关键词： digital twin simulation data model digitalisation cloud computing edge computing

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A Design Approach and Prototype Implementation for Factory Monitoring Based on Virtual and Augmented Reality at the Edge of Industry 4.0 21

A Design Approach and Prototype Implementation for Factory M...

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ieee 21st international conference on Industrial informatics (INDIN)

作者： Anagnostopoulos, Christos Mylonas, Georgios Fournaris, Apostolos P. Koulamas, Christos Athena Res & Innovat Ctr Ind Syst Inst Patras Greece

ISBN: (纸本)9781665493130

Virtual and augmented reality are currently enjoying a great deal of attention from the research community and the industry towards their adoption within industrial spaces and processes. However, the current design and implementation landscape is still very fluid, while the community as a whole has not yet consolidated into concrete design directions, other than basic patterns. Other open issues include the choice over a cloud or edge-based architecture when designing such systems. Within this work, we present our approach for a monitoring intervention inside a factory space utilizing both Virtual Reality (VR) and Augmented Reality (AR), based primarily on edge computing, while also utilizing the cloud. We discuss its main design directions, as well as a basic ontology to aid in simple description of factory assets. In order to highlight the design aspects of our approach, we present a prototype implementation, based on a use case scenario in a factory site, within the context of the EnerMan H2020 project.

关键词： augmented reality virtual reality extended reality Industry 4.0 edge computing

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Artificial Intelligence-based Service Chains Scheduling for Medical Emergency in Healthcare 7

Artificial Intelligence-based Service Chains Scheduling for ...

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7th international conference on Contemporary computing and informatics, IC3I 2024

作者： Soni, Mukesh Rusho, Maher Ali Byeon, Haewon Alghamdi, Azzah Hannan, Shaikh Abdul Dave, Parth Rameshchandra Dr. D. Y. Patil School of Science & Technology Tathawade Dr. D. Y. Patil Vidyapeeth Marashtra Pune India University of Colorado Department of Lockheed Martin Engineering Management BoulderCO80309 United States Inje University Department of Ai and Software & Medical Big Data Research Centre Gimhae50834 Korea Republic of Imam Abdalrhman Bin Faisal University College of Computer Science and Information Technology Computer Information Systems Department Khobar Saudi Arabia AlBaha University Faculty of Computing and Information AlBaha Saudi Arabia L. D. College of Engineering Department of Computer Engineering Gujarat Ahmedabad India

ISBN: (纸本)9798350350067

This study analyses the weekly scheduling challenge of health and medical information network service function chains to meet medical emergency categorization and grading needs. Emergency services are divided into four sorts by urgency and service area, with priorities and weights. The health and medical information network architecture, service model, and operation method are built accordingly. To reduce weighted completion time, a service function chain scheduling model is created. The function chain scheduling scheme is solved by matching game and Q -learning reinforcement learning algorithms for different issue scales. Finally, simulation studies demonstrate that this approach can accomplish graded medical emergency service, build health and medical information networks, and progress smart healthcare. © 2024 ieee.

关键词： Electronic health record

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Impedance Sensing-Centered Pervasive and Wearable Activity Recognition on Edge Devices

Impedance Sensing-Centered Pervasive and Wearable Activity R...

引用

ieee international conference on Pervasive computing and Communications (PerCom)

作者： Liu, Mengxi German Res Ctr Artificial Intelligence DFKI D-67663 Kaiserslautern Germany RPTU Kaiserslautern Landau Dept Comp Sci D-67663 Kaiserslautern Germany

ISBN: (纸本)9798350304367;9798350304374

Recent years have seen significant advancements in sensor-based pervasive and wearable activity recognition, primarily through the development of novel sensing modalities and the application of advanced machine learning algorithms. Despite this progress, the potential of impedance sensing in daily-life scenarios for pervasive and wearable activity recognition remains underexplored, particularly in contrast to its successful application in industrial and labor areas. Additionally, there is a lack of comprehensive studies on end-to-end optimization strategies from sensor to model, aimed at reducing both input and computational complexity of the neural network model, enabling it to not only run but also update efficiently on edge devices. This research project aims to bridge these gaps by investigating impedance sensing as a core technology for pervasive and wearable activity recognition in everyday environments and studying sensor-data-model co-optimization pipeline to enhance the performance and efficiency of these systems on edge devices.

关键词： impedance sensing activity recognition sensor fusion edge-computing

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An Adaptive Scheduling Method for Infrastructure Construction progress Based on Digital Twin 22

An Adaptive Scheduling Method for Infrastructure Constructio...

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22nd ieee international conference on Industrial informatics, INDIN 2024

作者： Liang, HaiSheng Wang, Yini Wei, Chuxi Yu, Songyuan Fang, Fang State Grid Shanghai Economic Research Institute State Grid Shanghai Municipal Electric Power Company Shanghai China School of Control And Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798331527471

The uncertainty of risk factors in infrastructure construction presents significant challenges to the management of construction progress. To effectively control construction progress while ensuring quality and reducing costs, we propose an adaptive scheduling method for infrastructure construction progress based on digital twin. First, we establish a digital twin model that reflects the construction progress by considering relevant progress information. Subsequently, taking into account the uncertainties associated with human factors, construction processes, and environmental factors, we develop a safety assessment method for power infrastructure and formulate a construction stoppage model. Then, we design an adaptive scheduling method that considers the uncertainties related to construction stoppage risks. Finally, the effectiveness and practicality of the proposed methods are validated through a comparative analysis of different cases. © 2024 ieee.

关键词： adaptive scheduling digital twin infrastructure construction

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