检索结果-内蒙古大学图书馆

18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Wang, Jinwei Huang, Wei Luo, Xiangyang Shi, Yung-Qing Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Information Security Institute Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Electrical Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030435745

In this paper, a feature based on the Markov model in quaternion discrete cosine transform (QDCT) domain is proposed for double JPEG compression detection. Firstly, a given JPEG image is extracted from blocked images to obtain amplitude and three angles (ψ, φ, and θ). Secondly, when extracting the Markov features, we process the transition probability matrix with the corresponding refinement. Our proposed refinement method not only reduces redundant features, but also makes the acquired features more efficient for detection. Finally, a support vector machine (SVM) is employed for NA-DJPEG compression detection. It is well known that detecting NA-DJPEG compressed images with (Formula Presented) is a challenging task, and when the images with small size (i.e., 64 × 64), the detection will be more difficult. The experimental result indicates that our method can still achieve a high classification accuracy in this case. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

On the ADEP and DOR Analysis of RIS-aided URLLC Systems with Partial CSI in Smart Factory

On the ADEP and DOR Analysis of RIS-aided URLLC Systems with...

引用

IEEE Globecom Workshops

作者： Tingnan Bao Haiming Wang Hong-Chuan Yang Wen-Jing Wang Mazen O. Hasna Lenovo Research + Institute Of Computing Technology Chinese Academy of Sciences Beijing China Lenovo Reseach Lenovo Group Limited Bejiing China Department of Electrical and Computer Engineering University of Victoria Victoria Canada Shaanxi Key Laboratory of Information Communication Network and Security XUPT Xi'an China Department of Electrical Engineering Qatar University Doha Qatar

ISBN: (数字)9781665423908

ISBN: (纸本)9781665423915

Factory automation applications impose stringent quality of service (QoS) over ultra-reliable and low-latency communication (URLLC) system. However, the existing wireless systems cannot meet the requirement for these mission-critical industrial internet-of-things (IIoT) applications. In this paper, we consider the reconfigurable intelligent surface (RIS)-aided URLLC systems in the smart factory. To facilitate the performance analysis of the practical situation, the presence of phase error at RIS is discussed. We analyze and derive approximate closed-form expression of average decoding error probability (ADEP) and the closed-form expression of performance limits de-lay outage rate (DOR) under our proposed scenario, respectively. Through analytical results and associated numerical examples, we demonstrate the effect of the number of reflecting elements at the RIS, channel blocklength and packet size in achieving high reliability and low latency. Therefore, the deployment of RIS can offer an attractive solution to enhance the reliability over URLLC systems in the smart factory.

关键词： Wireless communication Closed-form solutions Error probability Rician channels Quality of service Ultra reliable low latency communication Reconfigurable intelligent surfaces

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient UAV Trajectory Design for Backscatter Communication: A Deep Reinforcement Learning Approach

引用

China Communications 2020年第10期17卷 129-141页

作者： Yiwen Nie Junhui Zhao Jun Liu Jing Jiang Ruijin Ding School of Electronic and Information Engineering Beijing Jioatong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China Institute of Network Sciences and Cyberspace Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing 100084China Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and TelecommunicationsXi’an 710121China Institute for Artificial Intelligence Tsinghua University(THUAI)Beijing 100084China State Key Laboratory of Intelligent Technologies and Systems Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Department of AutomationTsinghua UniversityBeijing 100084China

Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and *** this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing ***,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among *** results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.

关键词： unmanned aerial vehicle(UAV) trajectory design backscatter communication deep reinforcement learning energy-efficient

来源：评论

学校读者我要写书评

暂无评论

Outage Analysis of Aerial Semi-Grant-Free NOMA Systems

arXiv

引用

arXiv 2022年

作者： Lei, Hongjiang Zhu, Chen Park, Ki-Hong Ansari, Imran Shafique Lei, Weijia Tang, Hong Kim, Kyeong Jin The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Lab of Mobile Communications Technology Chongqing400065 China Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and Telecommunications Shaanxi Xi’an710121 China Thuwal23955-6900 Saudi Arabia James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Mitsubishi Electric Research Laboratories CambridgeMA02139 United States

In this paper, we analyze the outage performance of Unmanned Aerial Vehicles (UAVs)-enabled downlink Non-Orthogonal Multiple Access (NOMA) communication systems with the Semi-Grant-Free (SGF) transmission scheme. A UAV provides coverage services for a Grant-Based (GB) user and one Grant-Free (GF) user is allowed to utilize the same channel resource opportunistically. The analytical expressions for the exact and asymptotic Outage Probability (OP) of the GF user are derived. The results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users’ quality of service requirements. Subsequently, an efficient Dynamic Power Allocation (DPA) scheme is proposed to relax such data rate constraints. The analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV’s location and altitude on the OP of the GF user. © 2022, CC BY.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Adaptive Fine-grained Access Control Method in Social Internet of Things

引用

International Journal of network security 2021年第1期23卷 42-48页

作者： Zhang, Hongbin Ma, Pengcheng Liu, Bin School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China Hebei Key Laboratory of Network and Information Security Hebei Normal China School of Economics and Management Hebei University of Science China Technology Research Center of Big Data and Social Computing Hebei University of Science China

Social Internet of Things (SloT), as a new carrier of integration of social and Internet of Things, applies the research results of social networks from different aspects of the Internet of Things. Different types of connected intelligent objects interact socially, compared with random data access between them, access control technology is more stringent. This paper integrates social attributes into attributebased access control of Internet of Things, initializes relational attribute tags, and labels social interest attributes for different objects, then quantifes tag similarity and implements initial access control authorization, integrates social attributes into game theory to dynamically adjust access control policies, so the adaptive finegrained division of access control under the Social Internet of Things is effectively realized. The experimental results show that our method can not only effectively carry out initial authorization according to tag similarity, but also further adaptively adjust the permission policy according to social attributes, and further meet the finegrained partition requirements of access control, which is ensure the effective implementation of access control under the Social Internet of things. © 2021. All Rights Reserved.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

TraCemop: Towards Federated Learning with Traceable Contribution Evaluation and Model Ownership Protection

引用

IEEE Transactions on Mobile computing 2025年

作者： Liu, Jingwei Zhou, Zihan Sun, Rong Liu, Lei Lu, Rongxing Dustdar, Schahram Niyato, Dusit Ministry of Education Engineering Research Center of Blockchain Technology Application and Evaluation China Xidian University Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'an710071 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China Xidian University Guangzhou Institute of Technology Guangzhou510555 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Queen's University School of Computing KingstonONK7L 2N8 Canada TU Wien Distributed Systems Group Austria UPF ICREA Barcelona Spain Nanyang Technological University School of Computer Science and Engineering Singapore

Federated Learning (FL) allows multiple clients to collaboratively train machine learning models without the need to share their local private data. As a result, it can effectively address the issue of data fragmentation. Nevertheless, insufficient evaluation of individual contributions and the lack of protections for both the intellectual property rights (IPR) of models and client privacy can greatly reduce clients' motivations in federated training. To address these challenges, this paper introduces the Traceable Contribution Evaluation and Model Ownership Protection (TraCemop) framework for federated learning, which allows each client to swiftly assess the contributions of others in each round, with integrated support for the traceability of evaluation results. To safeguard the intellectual property of models, a collective watermark is embedded in the global model. Additionally, a secure mechanism for verifying model ownership is also available in case of disputes. security analysis indicates that TraCemop is capable of resisting data reconstruction attacks as well as various types of model copyright infringements. Finally, we evaluate the proposed framework using two commonly-used datasets, and the experimental results show a significant improvement in the efficiency of contribution evaluation compared to existing methods. Meanwhile, IPR infringement tests on TraCemop reveal that the proposed framework is resilient against malicious efforts to monopolize model ownership. © 2002-2012 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Safeguarding Next Generation Multiple Access Using Physical Layer security Techniques: A Tutorial

arXiv

引用

arXiv 2024年

作者： Lv, Lu Xu, Dongyang Hu, Rose Qingyang Ye, Yinghui Yang, Long Lei, Xianfu Wang, Xianbin Kim, Dong In Nallanathan, Arumugam The State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China The School of Information and Communications Engineering Xi’an Jiaotong University Xi’an710049 China The Department of Electrical and Computer Engineering Utah State University LoganUT84322 United States The Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications Xi’an710121 China The School of Information Science and Technology Southwest Jiaotong University Chengdu610031 China The Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of School of Electronic Engineering and Computer Science Queen Mary University of London E1 4NS United Kingdom

Driven by the ever-increasing requirements of ultrahigh spectral efficiency, ultra-low latency, and massive connectivity, the forefront of wireless research calls for the design of advanced next generation multiple access schemes to facilitate provisioning of these stringent demands. This inspires the embrace of non-orthogonal multiple access (NOMA) in future wireless communication networks. Nevertheless, the support of massive access via NOMA leads to additional security threats, due to the open nature of the air interface, the broadcast characteristic of radio propagation as well as intertwined relationship among paired NOMA users. To address this specific challenge, the superimposed transmission of NOMA can be explored as new opportunities for security aware design, for example, multiuser interference inherent in NOMA can be constructively engineered to benefit communication secrecy and privacy. The purpose of this tutorial is to provide a comprehensive overview on the state-of-the-art physical layer security techniques that guarantee wireless security and privacy for NOMA networks, along with the opportunities, technical challenges, and future research trends. Copyright © 2024, The Authors. All rights reserved.

关键词： Radio waves

来源：评论

学校读者我要写书评

暂无评论

Research on Text Classification Based on BERT-BiGRU Model

引用

Journal of Physics: Conference Series 2021年第1期1746卷

作者： Qing Yu Ziyin Wang Kaiwen Jiang Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin China

Text classification is a typical application of natural language processing. At present, the most commonly used text classification method is deep learning. Meanwhile there are many difficulties in natural language processing, such as metaphor expression, semantic diversity and grammatical specificity. To solve these problems, this paper proposes the structure of BERT-BiGRU model. First, use the BERT model instead of the traditional word2vec model to represent the word vector, the word representation is calculated according to the context information, and it can be adjusted according to the meaning of word while the context information is fused. Secondly BiGRU model is attached to the BERT model, BiGRU model can extract the text information features from both directions at the same time. Multiple sets of experiments were set up and compared with the model proposed in this paper, according to the final experimental results, using the proposed BERT-BiGRU model for text classification, the final accuracy, recall and F1 score were all above 0.9. It shows that BERT-BiGRU model has good performance in the Chinese text classification task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Velocity-Driven Particle Swarm Optimization 19

Velocity-Driven Particle Swarm Optimization

引用

Proceedings of the 2019 8th International Conference on computing and Pattern Recognition

作者： Wei Li Yaochi Fan Qiaoyong Jiang Qingzheng Xu School of Computer Science and Engineering Xi'an University of Technology and Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China School of Computer Science and Engineering Xi'an University of Technology Xi'an China College of Information and Communication National University of Defense Technology Xi'an China

ISBN: (纸本)9781450376570

Particle swarm optimization (PSO) is an efficient nature-inspired optimization algorithm, which has been widely applied in many engineering fields. The performance of particle swarm optimization (PSO) has been significantly influenced by velocity update strategy. Traditionally, each particle updates its velocity based on its historical best experience and the global best experience, which may make the swarm lose its diversity and lead to premature convergence. To strengthen the performance of PSO, this paper proposes an improved PSO with the velocity-driven strategy (VD-PSO). In VD-PSO algorithm, the particles whose velocities are driven by better velocities focus on exploitation. The historical velocities, such as better velocities, may effectively characterize the landscape information of the optimization problems. In addition, the particles focus on exploration through information exchange amongst velocities. To verify the effectiveness of the proposed algorithm, experiments are conducted with CEC2014 test problems. The experimental results demonstrate the effectiveness of the proposed algorithm for solving the global optimization problems.

关键词： Evolutionary algorithms Velocity-driven strategy Particle swarm optimization Optimization problems

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Fault Diagnosis Method for Rolling Bearing Based on Attention and CNN

A Hybrid Fault Diagnosis Method for Rolling Bearing Based on...

引用

Robotics, Intelligent Control and Artificial Intelligence (RICAI), International Conference on

作者： Songtao Wang Qianlong Liu Jun Li Kun Liang Hui Cai Hangwei Tian Shandong Hi-Speed Construction Management Group Co. Ltd. Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd. Jinan China Shandong Hi-Speed Group Linteng Highway Co. Ltd. Jinan China School of Qilu Transportation Shandong University Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China

In the field of mechanical manufacturing, rolling bearings are important core components. To achieve stable rotational operation, improving diagnostic accuracy has become an urgent issue. In this paper, a hybrid fault diagnosis method is proposed, which combines attention and convolutional neural network and introduces Savitzky-Golay filter, called Savitzky-Golay Convolutional Attention network (SGCA-Net). The method adopts a dual-branch structure for rolling bearing fault diagnosis, which can effectively eliminate noise, and combines attention mechanism and convolutional neural network to perform feature learning on data. The experimental results show that the proposed method can accurately identify various faults, and has high accuracy and robustness.

关键词：

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：