检索结果-内蒙古大学图书馆

IEEE SoutheastCon conference

作者： Suski, William Card, Christopher Few, Brian Appl Engn Concepts Inc Eldersburg MD 21784 USA

ISBN: (纸本)9781665476119

Device authentication is an important element of any strong defense-in-depth strategy for securing cyber-physical, industrial control, and other critical infrastructure systems. However, the current stable of solutions available to perform device authentication are not suitable for deployment on many operational technology networks due to the power and processing limitations of legacy and state-of-the-art internet-of-Things devices. In this paper, we propose a machine learning method for passively and non-invasively authenticating or fingerprinting Ethernet devices, at the physical layer (PHY), using their transmitted signals. This technique exploits the unique, intrinsic physical features of a device that are created by the operational characteristics of its discrete physical components. These characteristics are imprinted on a device's communication signal, can be externally monitored to authenticate/authorize registered devices, and can quickly detect the introduction of unknown and/or unauthorized devices. We assess the performance of our proposed technique based on the discrimination power in a device classification scenario.

关键词： authentication intrusion detection network access control

来源：评论

学校读者我要写书评

暂无评论

QoE-Driven Adaptive Deployment Strategy of Multi-UAV networks Based on Hybrid Deep Reinforcement Learning

引用

IEEE internet OF THINGS JOURNAL 2022年第8期9卷 5868-5881页

作者： Zhou, Yi Ma, Xiaoyong Hu, Shuting Zhou, Danyang Cheng, Nan Lu, Ning Henan Univ Sch Artificial Intelligence Kaifeng 475004 Peoples R China Henan Univ Int Joint Res Lab Cooperat Vehicular Networks Hen Kaifeng 475004 Peoples R China Xidian Univ State Key Lab ISN Xian 710071 Peoples R China Xidian Univ Sch Telecommun Engn Xian 710071 Peoples R China Queens Univ Dept Elect & Comp Engn Kingston ON K7L 3N6 Canada

Unmanned aerial vehicles (UAVs) serve as aerial base stations to provide controlled wireless connections for ground users. Due to their constraints on both mobility and energy consumption, a key problem is how to deploy UAVs adaptively in a geographic area with changing traffic demand of mobile users, while meeting the aforementioned constraints. In this article, we propose a quality of Experience (QoE)-driven and energy-efficient adaptive deployment strategy for multi-UAV networks based on hybrid deep reinforcement learning (DRL) to solve the problem of incomplete information game, where the UAVs can adjust their moving directions and distance to serve users who move randomly in the target area. Through the hybrid DRL with centralized training and distributed testing, UAVs can be trained offline to obtain the global state information and learn a completely distributed control strategy, with which each UAV only needs to take actions based on its observed state in the real deployment to be fully adaptive. Moreover, in order to improve the speed and effect of learning, we improve hybrid reinforcement learning, by adding genetic algorithms and temporal difference error-based resampling optimization mechanism. The simulation results show that the hybrid DRL algorithm has better efficiency and robustness in multi-UAV control, and has better performance in terms of QoE, energy consumption, and average throughput, by which average throughput can be increased by 20%-60%.

关键词： Games Reinforcement learning Unmanned aerial vehicles Optimization Adaptive systems Throughput quality of experience Adaptive deployment deep reinforcement learning (DRL) efficiency optimization game theory quality of Experience (QoE) driven unmanned aerial vehicle (UAV) network

来源：评论

学校读者我要写书评

暂无评论

Research on IoT Device Fingerprint Recognition in Grid Power System Based on Few-Shot Learning 5

Research on IoT Device Fingerprint Recognition in Grid Power...

引用

2023 5th International conference on Artificial Intelligence and Computer Applications, ICAICA 2023

作者： Zhang, Liang Ge, Minhui Zou, Futai East Branch of State Grid Corporation of China Shanghai China Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350323313

IoT smart devices play a pivotal role in power grid systems, contributing to efficient monitoring and control. However, the diverse range of IoT device types and the scarcity of samples pose challenges for accurate device recognition. In this context, we propose a method tailored to small-sample scenarios, addressing the vital need for robust detection. Our approach leverages the Triplet-loss concept to construct a Triplet-CNN feature extractor, harnessing the power of CNN networks for enhanced feature extraction and achieving the construction of a privacy recognition method for IoT devices under small sample conditions. Our model demonstrates exceptional performance, achieving an impressive 84% detection accuracy with a minimal sample size of just 20, significantly surpassing traditional deep learning algorithms. © 2023 IEEE.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

Reliability Analysis of networked control systems Considering Data Link performance Correlation 12

Reliability Analysis of Networked Control Systems Considerin...

引用

12th International conference on quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Liang, Sheng Wang, Ying Bao, Xiaoyan Shi, Jialiang Colledge of Mechanical Engineering Inner Mongolia University of Technology Hohhot China

ISBN: (纸本)9781839538360

Digital networked control systems are of growing importance in safety-critical systems and perform indispensable function in most complex systems today. networked degradation such as transmission delay cause such systems to fail to satisfy performance requirements, and eventually affect the overall ***, it is very important to obtain a reliability evaluation model of the entire network system based on the performance of transmission links. However, the existing networked control system performance reliability evaluation models often regard the transmission links as independent, ignoring the relevance of data transmission between *** the perspective of link correlation, this paper proposes a new method of fusing data-driven and compound Archimedes Copula function modeling to analyze the reliability of networked control system performance. Finally, a networked control system example is provided to illustrate the effectiveness of the model and method. © 2022 IEEE.

关键词： networked control systems

来源：评论

学校读者我要写书评

暂无评论

(POSTER) A Holistic IoT-Enabled Approach for Indoor Air quality control 19

(POSTER) A Holistic IoT-Enabled Approach for Indoor Air Qual...

引用

19th Annual International conference on Distributed Computing in Smart systems and the internet of Things, DCOSS-IoT 2023

作者： Kalioras, Fotios Filios, Gabriel Karatzas, Stylianos Nikoletseas, Sotiris University of Patras Department of Computer Engineering and Informatics Greece University of Patras Computer Technology Institute and Press Diophantus Department of Computer Engineering and Informatics Greece University of Patras Department of Civil Engineering Greece

ISBN: (纸本)9798350346497

Indoor air quality (IAQ) is an important yet often overlooked aspect of public health, with poor IAQ contributing to a significant number of diverse health problems worldwide. Existing air quality standards have failed to fully address the problem, however emerging technologies in the field of IoT have demonstrated promise in effectively addressing this issue. This concept paper advocates a hybrid hierarchy system for IAQ monitoring that incorporates both offline and online connectivity. The system utilizes sensing elements that can perform a wide range of functions, including autocalibration, pollution event detection, and more, autonomously from the network. By combining a gateway device, the system's capabilities are enhanced, providing increased data granularity, additional calibration and sensing options as well as connection with Building Management systems (BMS). Furthermore, by connecting the gateway to the cloud, the system can perform more advanced data analysis and machine learning, providing users with insights into not only air quality but also general environmental quality. Key features of the envisioned system include the integration of subjective perception of pollution via crowdsourcing, a TinyML technology at the edge, digital twins, and an optimised redundancy of sensors that can alleviate poor accuracy and drift as well as capture the spatial dispersion of pollution. © 2023 IEEE.

关键词： Crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

MULTI-PRIORITY MAC PROTOCOL FOR TERAHERTZ WIRELESS LOCAL AREA network 34

MULTI-PRIORITY MAC PROTOCOL FOR TERAHERTZ WIRELESS LOCAL ARE...

引用

34th Chinese control and Decision conference (CCDC)

作者： Ding, Yuanming Liu, Yang Feng, Jianxin Dalian Univ Key Lab Commun & Network Dalian 116622 Peoples R China Dalian Univ Coll Informat Engn Dalian 116622 Peoples R China

ISBN: (纸本)9781665478960

In order to solve the problem that IEEE802.15.3c protocol is designed without considering the characteristics oflarge traffic network environment in terahertz wireless local area network, a multi priority MAQMP-MAC) protocol is proposed. The MO-MAC protocol uses a backoff algorithm to determine data priority based on nodes and services, dynamically divides Channel Time Allocation (CTA), and uses a backpack algorithm to allocate time slot resources in a competitive access period (CAP). Simulation results show that under the condition of high load, compared with other protocols, this protocol can reasonably allocate time slot resources, has better network performance, and ensures the quality of service of high priority services.

关键词： Terahertz Communication Multiple Priority Time Slot Allocation

来源：评论

学校读者我要写书评

暂无评论

Research on Geospatial Object Recognition Algorithm in Power Transmission and Transformation Engineering Based on FIseg-YOLO 1

引用

8th International conference on Life System Modeling and Simulation, LSMS 2024 and 8th International conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Ouyang, Peng Pi, Yufei Zhang, Pengcheng Zhang, Kun School of Electrical Engineering and Automation Nantong University Nantong China Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong Institute of Technology Jiangsu Nantong China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

The preliminary work of power transmission and transformation engineering design tasks relies on the precise survey of terrain to ensure the high-quality completion of design tasks. Therefore, developing a technology that can accurately and efficiently survey the construction area has become a hot topic in the field of electrical design research. However, identifying the location and precise boundaries of geospatial targets of different scales and densities from high-resolution natural environment images captured by drones remains a challenge. To address this issue, we improved upon the YOLOv8 algorithm by incorporating the concept of the YOLACT algorithm, proposing a novel instance segmentation algorithm—FIseg-YOLO, specifically designed for recognizing geospatial targets in power transmission and transformation line projects. This algorithm integrates various attention mechanism modules in the backbone network, effectively improving the accuracy of target recognition against complex backgrounds. Simultaneously, we optimized the neck network structure by enhancing the multi-path fusion of the network, achieving multi-level feature fusion between different layers. Additionally, the algorithm adds a multi-scale detection head to the basic network structure to extract shallow information from the input image and combine it with the feature fusion network to detect objects across a broader scale. Experimental validation on the geospatial orthophoto dataset shows that the mAP@.5 of the FIseg-YOLO model reached 67.3%, a 6.6% increase compared to the YOLOv8 base model, indicating a significant improvement in model performance. This improvement is of great significance for enhancing the efficiency of preliminary survey tasks in power transmission and transformation engineering. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Hyper Parameter Optimization for Ensemble Techniques in Classifying QUIC Traffic

Hyper Parameter Optimization for Ensemble Techniques in Clas...

引用

Cognitive Robotics and Intelligent systems (ICC - ROBINS), International conference on

作者： Christina Merlin Getzi Jeba Leelipushpam Paulraj Immanuel Johnraja Jebadurai Elvina Sharon Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

The number of internet-based devices is increasing exponentially in day-to-day life. Higher levels of usage results in increased network traffic. It affects the network performance rate and quality, thereby leaving a threat to security. network traffic classification is the process that classifies different types of network traffic and identifies solutions to overcome these issues. Efficient classification of Quick UDP internet Connections (QUIC) traffic is crucial for network management. This study focuses on optimizing classification accuracy through ensemble techniques and hyperparameter tuning. Ensemble methods, like bagging and boosting, combine multiple base models to enhance the performance. Hyperparameter optimization fine-tunes these models, controlling their behavior and improving classification accuracy. The research contributes insights into effective ensemble modeling for network protocols, offering practical guidance for QUIC traffic management and optimization. It underscores the significance of hyperparameter optimization in advancing QUIC network classification accuracy, which is crucial for modern internet communication.

关键词： Systematics Protocols Telecommunication traffic Predictive models Hyperparameter optimization internet Space exploration

来源：评论

学校读者我要写书评

暂无评论

Application Service Monitoring in Cellular IoT network 22

Application Service Monitoring in Cellular IoT Network

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Tangudu, Narendranath Durga Shah, Sapan Pramodkumar Seenivasan, Varadarajan Ambati, Venkata Anil Kumar Pattan, Basavaraj Jayawant Yoon, Seungil Vankayala, Satya Kumar Samsung R&d Institute Bangalore India Samsung Electronics Seoul Korea Republic of

ISBN: (纸本)9798331508050

With 5G a reality, communication is not only getting faster and better, but also the new verticals, which were so far not serviced by the cellular industry, are supported. One of the areas where 5 G has promising impact is enabling the internet of Things (IoT) communication. With higher spectrum and bandwidth, 5G enables massive number of devices to connect to the IoT networks. At the same time, the exponential growth of the number of connected devices puts unprecedented load on cellular infrastructure. Further, 5G enables IoT applications to control more devices remotely where low latency and high throughput are critical performance criteria - like healthcare and factory applications. For such applications, it is essential that the application service remains available and be responsive always. Continuous monitoring at all the layers is critical in ensuring the seamless and uninterrupted service availability, thus improving the user experience and efficient use of resources. In this paper, the authors explain the benefits of Application Service Monitoring (ASM) in coordination with the underlying transport in providing the best quality of experience for the user through a framework using 3GPP Service Enabler Architecture Layer (SEAL). The paper also provides a mathematical model of the quality of Service (QoS) adaptation through network and Vertical Application Layer (VAL) coordination feature of framework and substantiate the same with the simulation and its results. The paper finally provides simulation results explaining the benefits of using ASM framework with SEAL. © 2025 IEEE.

关键词： 3GPP SEAL 5G Application Service Monitoring IoT OneM2M

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Blockchain-based Resource Access control Architecture and Scheme for IoT Devices 96

Hierarchical Blockchain-based Resource Access Control Archit...

引用

IEEE 96th Vehicular Technology conference (VTC-Fall)

作者： Chai, Rong Jiang, Wenhang Yang, Xizheng Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China

ISBN: (纸本)9781665454681

Traditional access control schemes in internet of things (IoT) systems have long been faced with security problems such as single point of failure, data tampering and cross-domain access. In this paper, we study the access control problem in an IoT system composed of multiple domains. Applying blockchain technology, we propose a hierarchical blockchain-based access control architecture which consists of two layers of blockchain networks, i.e., global blockchain network and local blockchain network. Based on the proposed architecture, the processes of inter-domain and intra-domain access control are examined, respectively. In order to achieve the secure access of user data in the proposed architecture, we further present a trust-value based access control strategy. To examine the performance of proposed architecture and strategy, we set up an access control simulation platform based on Hyperledger Fabric and verify the feasibility of the proposed architecture and strategy.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：