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arXiv 2022年

作者： Shi, Wei Xu, Wei You, Xiaohu Zhao, Chunming Wei, Kejun The National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China The China Academy of Information and Communications Technology China

Internet-of-Everything (IoE) has gradually been recognized as an integral part of future wireless networks. In IoE, there can be an ultra-massive number of smart devices of various types to be served, imposing multi-dimensional requirements on wireless communication, sensing, and security. In this article, we provide a tutorial overview of the promising intelligent reflection communication (IRC) technologies, including reconfigurable intelligent surface (RIS) and ambient backscatter communication (AmBC), to support the requirements of IoE applications beyond the fifth-generation (5G) wireless communication network. Specifically, we elaborate on the benefits of IRC-assisted IoE in the context of the space-air-ground integrated communications and green communications, which are regarded as key features of supporting future IoE application from society and industries. Furthermore, we envision that the IRC-assisted communication and sensing can mutually benefit each other and articulate multiple ways of enhancing the security in IoE by the IRC. Numerical results help illustrate the importance of the IRC in unfavorable secrecy environments. Finally, open research issues and challenges about the IRC-assisted IoE are presented. Copyright © 2022, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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Concept and Research Framework for Coordinated Situation Awareness and Active Defense of Cyber-physical Power Systems Against Cyber-attacks

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Journal of Modern Power Systems and Clean Energy 2021年第3期9卷 477-484页

作者： Ming Ni Manli Li Jun’e Li Yingjun Wu Qi Wang the NARI Group Corporation(State Grid Electric Power Research Institute) NARI Technology Co.Ltd.and the State Key Laboratory of Smart Grid Protection and ControlNanjing 211106China the School of Cyber Science and Engineering Wuhan Universityand the Key Laboratory of Aerospace Information Security and Trusted Computing of the Ministry of EducationWuhan 430072China the College of Energy and Electrical Engineering Hohai UniversityNanjing 211100China the School of Electrical Engineering Southeast UniversityNanjing 210096China

Due to the tight coupling between the cyber and physical sides of a cyber-physical power system(CPPS),the safe and reliable operation of CPPSs is being increasingly impacted by cyber *** situation poses a challenge to traditional security defense systems,which considers the threat from only one side,i.e.,cyber or *** cope with cyberattacks,this paper reaches beyond the traditional one-side security defense systems and proposes the concept of cyber-physical coordinated situation awareness and active defense to improve the ability of *** example of a regional frequency control system is used to show the validness and potential of this ***,the research framework is presented for studying and implementing this ***,key technologies for cyber-physical coordinated situation awareness and active defense against cyber-attacks are introduced.

关键词： Cyber-physical power system(CPPS) cyber security cyber-attack situation awareness active defense

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Smart Meter Intrusion Detection Based on APSO-DBN Model 1

Smart Meter Intrusion Detection Based on APSO-DBN Model

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1st International Conference on Smart City Challenges and Outcomes for Urban Transformation, SCOUT 2021

作者： Zhang, Yi-Ying Luo, Jian He, Yeshen Ma, Shengguo Liang, Kun Liu, Zhu Internet of Things and Information Security Laboratory Tianjin University of Science & Technology Tianjin300457 China Shenzhen Guodian Technology Communication Co. Ltd. China Cridcom CO. LTD. Shenzhen518110 China Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665407670

With the continuous development of network technology and information technology, more and more attention has been paid to the network security of smart meters. When facing the network intrusion data of smart meters, the data has large-scale, high-dimensional and nonlinear intrusion detection problems. This paper proposes a model about the network intrusion model, which is based on Adaptive Particle Optimization (APSO) Deep Belief Network (DBN). First, construct a classification model based on DBN algorithm. Next, accelerate the optimization of DBN by using APSO algorithm, and calculate the number of hidden layer nodes to obtain the DBN model structure of the best hidden layer. Finally, construct the intrusion detection model of smart meter based on APSO-DBN. © 2021 IEEE.

关键词： Smart meters

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Large Generative Model Assisted 3D Semantic communication

arXiv

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arXiv 2024年

作者： Jiang, Feibo Peng, Yubo Dong, Li Wang, Kezhi Yang, Kun Pan, Cunhua You, Xiaohu Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China School of Information Science and Engineering Hunan Normal University Changsha China Changsha Social Laboratory of Artificial Intelligence Hunan University of Technology and Business Changsha China The Department of Computer Science Brunel University London United Kingdom The School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Changchun Institute of Technology China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Frontiers Science Center for Mobile Information Communication and Security National Mobile Communications Research Laboratory Southeast University Nanjing China The Purple Mountain Laboratories Nanjing China

Semantic communication (SC) is a novel paradigm for data transmission in 6G. However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extraction;2) Latent semantic redundancy;and 3) Uncertain channel estimation. To address these issues, we propose a Generative AI Model assisted 3D SC (GAM-3DSC) system. Firstly, we introduce a 3D Semantic Extractor (3DSE), which employs generative AI models, including Segment Anything Model (SAM) and Neural Radiance Field (NeRF), to extract key semantics from a 3D scenario based on user requirements. The extracted 3D semantics are represented as multi-perspective images of the goal-oriented 3D object. Then, we present an Adaptive Semantic Compression Model (ASCM) for encoding these multi-perspective images, in which we use a semantic encoder with two output heads to perform semantic encoding and mask redundant semantics in the latent semantic space, respectively. Next, we design a conditional Generative adversarial network and Diffusion model aided-Channel Estimation (GDCE) to estimate and refine the Channel State information (CSI) of physical channels. Finally, simulation results demonstrate the advantages of the proposed GAM-3DSC system in effectively transmitting the goal-oriented 3D scenario. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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Deployment of NRF in the Docker and Kubernetes - Based NFV Platform

Deployment of NRF in the Docker and Kubernetes - Based NFV P...

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Workshops of the 34th International Conference on Advanced information Networking and Applications, WAINA 2020

作者： Huang, Di Xu, Zhan Tian, Zhigang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9783030440374

Network Function Virtualization (NFV) which is one of the core technologies plays an important role in reality. NFV permits using Virtual Network Functions (VNF) as software components on top of a virtualization system (i.e., Virtual Machines or Containers) hosted in a cloud, which makes network services and functions deployed in high flexibility and elasticity. Therefore, based on this design concept, in 5G core networks, NRF (Network Repository Function), which was implemented in a server, supports network function of registering and monitoring conditions. It achieves automatic management, selection, and scalability of network function services. In this paper, NRF is deployed in Docker and Kubernetes-based NFV platform in the form of JSON + HTTP/2.0 that supports service discovery function. The performance is tested on a hardware platform, including Network Function (NF) Register, NF Update and NF Deregister. From the testing data, we can find that the NRF in the Docker and Kubernetes-based NFV platform is better than only Docker implemented platform. © 2020, Springer Nature Switzerland AG.

关键词： Network function virtualization

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DistTune: Distributed fine-grained adaptive traffic speed prediction for growing transportation networks

arXiv

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arXiv 2021年

作者： Lee, Ming-Chang Lin, Jia-Chun Gran, Ernst Gunnar Department of Information Security and Communication Technology Norwegian University of Science and Technology Gjøvik Norway Simula Research Laboratory Fornebu Norway

Over the past decade, many approaches have been introduced for traffic speed prediction. However, providing fine-grained, accurate, time-efficient, and adaptive traffic speed prediction for a growing transportation network where the size of the network keeps increasing and new traffic detectors are constantly deployed has not been well studied. To address this issue, this paper presents DistTune based on Long Short-Term Memory (LSTM) and the Nelder-Mead method. Whenever encountering an unprocessed detector, DistTune decides if it should customize an LSTM model for this detector by comparing the detector with other processed detectors in terms of the normalized traffic speed patterns they have observed. If similarity is found, DistTune directly shares an existing LSTM model with this detector to achieve time-efficient processing. Otherwise, DistTune customizes an LSTM model for the detector to achieve fine-grained prediction. To make DistTune even more time-efficient, DistTune performs on a cluster of computing nodes in parallel. To achieve adaptive traffic speed prediction, DistTune also provides LSTM re-customization for detectors that suffer from unsatisfactory prediction accuracy due to for instance traffic speed pattern change. Extensive experiments based on traffic data collected from freeway I5-N in California are conducted to evaluate the performance of DistTune. The results demonstrate that DistTune provides fine-grained, accurate, time-efficient, and adaptive traffic speed prediction for a growing transportation network. © 2021, CC BY-NC-ND.

关键词： Speed

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Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless Networks

TechRxiv

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TechRxiv 2022年

作者： Zhang, Yuanyu Zheng, Zhumeng He, Ji Zhao, Shuangrui Qu, Qianyue Shen, Yulong Jiang, Xiaohong School of Computer Science and Technology Xidian University Shaanxi Xi’an China Shannxi Key Laboratory of Network and System Security China The Beijing Sunwise Information Technology Ltd Beijing Institute of Control Engineering Beijing China The Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan School of Systems Information Science Future University Hakodate Hokkaido Hakodate Japan

While the millimeter-wave (mmWave) communication is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack. © 2022, CC BY.

关键词： Millimeter waves

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LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection

arXiv

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arXiv 2024年

作者： Tian, Jiwei Shen, Chao Wang, Buhong Xia, Xiaofang Zhang, Meng Lin, Chenhao Li, Qian Ministry of Education Key Laboratory for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Xi’an China Air Traffic Control and Navigation College Air Force Engineering University Xi’an China Information and Navigation College Air Force Engineering University Xi’an China School of Computer Science and Technology Xidian University Xi’an China

—Deep learning methods can not only detect false data injection attacks (FDIA) but also locate attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on deep learning vulnerabilities have been studied in the field of single-label FDIA detection, the adversarial attack and defense against multi-label FDIA locational detection are still not involved. To bridge this gap, this paper first explores the multi-label adversarial example attacks against multi-label FDIA locational detectors and proposes a general multi-label adversarial attack framework, namely muLti-labEl adverSarial falSe data injectiON attack (LESSON). The proposed LESSON attack framework includes three key designs, namely Perturbing State Variables, Tailored Loss Function Design, and Change of Variables, which can help find suitable multi-label adversarial perturbations within the physical constraints to circumvent both Bad Data Detection (BDD) and Neural Attack Location (NAL). Four typical LESSON attacks based on the proposed framework and two dimensions of attack objectives are examined, and the experimental results demonstrate the effectiveness of the proposed attack framework, posing serious and pressing security concerns in smart grids. © 2024, CC BY.

关键词： Location

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Two-Stage Task Planning Based on Resource Interchange in Space information Networks 15th

Two-Stage Task Planning Based on Resource Interchange in Spa...

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15th EAI International Conference on communications and Networking, ChinaCom 2020

作者： Liu, Runzi Li, Jing Ji, Xiang Wu, Weihua Zhou, Di Zhang, Yan School of Information and Control Engineering Xi’an University of Architecture and Technology Xi’an710055 China School of Telecommunications Engineering Xidian University Xi’an710071 China Science and Technology on Communication Networks Laboratory CETC the 54th Research Institute Shijiazhuang050081 China

ISBN: (纸本)9783030677190

The high computational complexity and the mismatch between the space-time distribution of tasks and resources raise great challenges on task planning in space information networks (SINs). This paper studies the task planning problem in SINs by exploiting resource interchange to handle the bottleneck resources. First of all, we use time-varying resource graph to capture the dynamic coordination relationship among resources in SIN. Then, we explore resource interchange and derive its quantitative condition. On this basis, an optimization model for task planning based on resource interchange is formulated. Furthermore, we decompose the task planning problem into two stages for global optimization and local adjustment, and develop the algorithms respectively. Finally, simulation results show that compared with existing works the proposed algorithm strikes a better balance between the number of completed tasks and computational complexity. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Computational complexity

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Modeling Building Method of Lissajous Figure Reversal Period Based on the Group Quantization Phase Processing

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Chinese Journal of Electronics 2019年第3期28卷 551-558页

作者： DU Baoqiang LI Songlin SUN Xiyan FU Qiang School of Electronic Information Engineering Zhengzhou University of Light Industry School of Information and Communication Guilin University of Electronic Technology Science and Technology on Electronic Information Control Laboratory

To deeply understand the essential relationship between two different-frequency signals and explore the phase synchronization law in frequency standard comparison, a novel modeling building method of Lissajous figure reversal period is proposed based on the group quantization phase processing. The relationships between the Lissajous figure reversal period and group period are revealed. The frequency deviation and nominal frequency of the measured signal are obtained using the group period and number of inflection point in the Lissajous figure. The results of a frequency standard comparison can accurately achieved using the frequency deviation. A lot of noise problems introduced by the frequency divider, frequency multiplier and frequency mixer are solved in the traditional frequency standard comparison, and the high-precision frequency standard comparison results can be quickly obtained using the proposed method. The experimental results show that a close relationship exists among the Lissajous figure reversal period, group period and frequency *** measured frequency can be precisely calculated using the relationship, and the frequency stability of system can reach the E-112/s level.

关键词： Lissajous figure Reversal period Group quantization Frequency stability

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