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Concise RingCT Protocol Based on Linkable Threshold Ring Signature

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2024年第5期21卷 5014-5028页

作者： Duan, Junke Zheng, Shihui Wang, Wei Wang, Licheng Hu, Xiaoya Gu, Lize Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing 100081 Peoples R China

Ring Confidential Transactions (RingCT) is a typical privacy-preserving protocol for blockchain, which is used for the most popular anonymous cryptocurrency Monero in recent years. RingCT provides the user's identity anonymity based on the linkable ring signature. At the cost of that, the transaction size is increased linearly to the involved users. In this article, we aim to overcome this inefficient aspect of RingCT by introducing the linkable threshold ring signature (LTRS). We first propose a construction of threshold ring signatures for homomorphic cryptosystems, and present an efficient instantiation based on the intractability assumption of the discrete logarithm problem. Based on this framework, an efficient LTRS scheme and a novel construction of the RingCT protocol are presented. Our proposed RingCT protocol enables multiple payers to co-construct an anonymous transaction without revealing their secret account keys, and it is more concise under multiple input accounts. For a transaction with a ring size of 100 and the input accounts number of 64, the communication overhead is about 4% of the original RingCT protocol.

关键词： Protocols Security Blockchains Public key Symbols Generators Electronic mail Ring signature linkable threshold ring signature anonymity RingCT blockchain cryptocurrency

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CarveNet: a channel-wise attention-based network for irregular scene text recognition

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INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION 2022年第3期25卷 177-186页

作者： Wu, Guibin Zhang, Zheng Xiong, Yongping Beijing Univ Posts & Telecommun State Key Lab Switching & Networking Technol Beijing 100876 Peoples R China

Although it has achieved considerable progress in recent years, recognizing irregular text in natural scene is still a challenging problem due to the distortion and background interference. The prior works use either spatial transformation network(STN) or 2D Attention mechanism to improve the recognition accuracy. However, STN-based methods are not robust as the limited network capacity while 2D Attention-based methods are highly interfered by fuzziness, distortion and background. In this paper, we propose a text recognition model CarveNet which consists of three substructures: feature extractor, feature filter and decoder. Feature extractor utilizes FPN (Feature Pyramid Network) to aggregate multi-scale hierarchical feature maps and obtain a larger receptive field. Then, feature filter composed of stacked Residual Channel Attention Block is followed to separate text features from background interference. The 2D self-attention-based decoder generates the text sequence according to the output of feature filter and the previously generated symbols. Extensive evaluation results show CarveNet achieves state-of-the-art on both regular and irregular scene text recognition benchmark datasets. Compared with the previous work based on 2D self-attention, CarveNet achieves accuracy increases of 2.3 and 4.6% on irregular dataset SVTP and CT80.

关键词： Scene text recognition Optical character recognition Channel-wise attention Transformer

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Three-Dimensional Trajectory Designs for Unmanned Aerial Vehicle-Enabled Communications With Kinematic Constraints

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IEEE TRANSACTIONS ON VEHICULAR technology 2022年第10期71卷 10910-10922页

作者： Zhang, Xian Liu, Chenxi Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

In this paper, we propose novel three-dimensional (3-D) trajectory designs for unmanned aerial vehicle (UAV)-enabled communications, where a single UAV needs to adaptively determine its locations in a timely manner in order to provide radio coverage to terrestrial mobile users. Taking the kinematic constraints on the speed and the turning angle of the UAV into account, we formulate a UAV trajectory optimization problem to maximize the average throughput of the considered system, while satisfying the coverage requirements of the mobile users simultaneously. To solve this NP-hard problem, we first propose an offline trajectory design algorithm that can determine the whole trajectory of the UAV, assuming that the global information (e.g., channel state information and the users' location information at all time slots) is known a priori. Then, we propose two low-complexity online algorithms that utilize the past and current information of the system only. Numerical results are provided to verify the effectiveness of our proposed algorithms. Moreover, we show that our proposed online algorithms can achieve almost the same system performance as the proposed offline algorithm, while inducing significant lower computational complexity.

关键词： Autonomous aerial vehicles Kinematics Turning Trajectory optimization Trajectory planning Resource management Wireless networks Unmanned aerial vehicle trajectory design user mobility UAV kinematic constraints

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Reliability and Energy Balanced Computation Resource Allocation Mechanism in Federated Learning System for AI-enabled IoT Businesses

Reliability and Energy Balanced Computation Resource Allocat...

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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Qi, Yonghao Xu, Siya Qi, Feng Yu, Peng Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

ISBN: (纸本)9798350310900

With the advancement and widespread adoption of Artificial Intelligence (AI) and Internet of Things (IoT) technology, machine learning (ML) can be leveraged in automated factories to enable intelligent robot fault detection and recognition. As an emerging distributed machine learning framework, federated learning (FL) enables collaborative model training while safeguarding the privacy of user data. However, FL encounters various challenges, including the lack of stable energy supply to maintain continuous training and the existence of malicious terminals in the system. These situations could result in issues such as free-riding attacks and robots running out of energy during the training process. Hence, this paper presents a reliability and energy balanced computation resource allocation mechanism in FL system for IoT businesses. Firstly, a training latency and model contribution based reputation evaluation model is proposed to reveal the reliability of IoT terminals. Then, a training client reliable selection and delayed admission strategy is proposed, which takes into account both the reputation and energy consumption, aiming at enabling terminals with highquality data and low energy capacity to keep contributing to the model during the later training stage. Especially, we integrate reputation and computing capability of IoT terminals to decide the freshness level of the allocated FL global model, which can effectively defend against free-riding attacks. The simulation results verify that the proposed mechanism outperforms non-delayed/partial-delayed admission mechanisms in terms of model quality and system stability.

关键词： federated learning reputation delayed admission client selection model freshness

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Two grids are better than one: Hybrid indoor scene reconstruction framework with adaptive priors

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NEUROCOMPUTING 2025年 618卷

作者： Bai, Boyuan Qiao, Xiuquan Lu, Ping Zhao, Hongru Shi, Wenzhe Zhang, Hengjia Huang, Yakun Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China State Key Lab Mobile Network & Mobile Multimedia T Shenzhen 518055 Peoples R China Zhengzhou Univ Sch Comp & Artificial Intelligence Zhengzhou 450001 Peoples R China

Indoor scene reconstruction from multi-view images is a pivotal technology within the field of robotics and augmented reality. Previous researches have predominantly focused on neural radiance fields aided by geometric monocular priors. However, due to the inductive smoothness bias introduced by deep Multi- Layer Perceptron (MLP) networks, these methods struggle to recover the scene surface with complex and fine geometry details. Additionally, when used as additional supervision signals during optimization, priors indifferent regions make different contributions. Simply incorporating them in all regions may lead to a decrease in the accuracy. To tackle these issues, we present a generic end-to-end framework named AdaptSurf, which combines Signed Distance Field (SDF) voxel grids and feature voxel grids to enhance the capability of reconstructing accurate geometry details, respectively. Furthermore, we design a policy network to adaptively enable the estimated depth or normal priors to supervise the learning process, which improves the reconstruction accuracy and accelerates neural surface reconstruction. Qualitative and quantitative experiments show that AdaptSurf yields high-quality surfaces, especially for fine-grained details and smooth regions. Furthermore, the policy network exhibits an interpretable behavior that depends on the voxel features, which helps to improve the quality of surface reconstruction.

关键词： 3D reconstruction NeRF Geometric priors Volume rendering

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In-Network DDoS Mitigation Mechanism for Vehicle Road Cooperation Network With Victim-Centric Approach

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IEEE INTERNET OF THINGS JOURNAL 2025年第11期12卷 15514-15532页

作者： Liu, Yan Shao, Sujie Guo, Shaoyong Zang, Zhibin Chen, Xingyu Qi, Feng Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China State Grid Informat & Commun Ind Grp Co Ltd Beijing 102211 Peoples R China

Vehicle road cooperation (VRC) services closely related to personal safety impose stringent requirements on reliability and real-time performance. However, the growing trend of vehicle to network (V2N) connections has significantly intensified the threat of distributed Denial of Service (DDoS) to the end-cloud communication links. To address this challenge, this article introduces a comprehensive DDoS defense architecture for VRC, named in-network DDoS-oriented Balancer, Inspector, and Filter (IDBIF). Leveraging programmable switches, IDBIF adopts an in-network mode to dynamically mitigate volumetric DDoS traffic in real-time, which coordinates three data plane functions for traffic processing: 1) load balancing;2) packet inspection;and 3) traffic filtering. Our work faces the starved data plane resources and establishes the problem model for high reliability requirements of VRC services when subjected to DDoS attacks. Furthermore, we developed a multiagent hierarchical structure policy gradient (MAHSPG) algorithm that combines the inherent characteristics of DDoS attacks to tackle the runtime deployment of high-dimensional and heterogeneous defense function chains. Simulation experiment results show that the proposed approach alleviates the data plane resource bottleneck and improves the DDoS defense effect by 24.80%, highlighting its advantages in ensuring reliable VRC services.

关键词： Computer crime Denial-of-service attack Prevention and mitigation Collaboration Pipelines Real-time systems Filtering Roads Reliability Inspection Cloud service security distributed Denial of Service (DDoS) programmable switch vehicle road cooperation (VRC)

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Energy Aware Virtual Network Migration

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2022年第2期10卷 1173-1189页

作者： Zhang, Zhongbao Cao, Huafeng Su, Sen Li, Weitian Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

In network virtualization, one of the key problems is to embed a sequence of virtual networks with both node and link constraints onto the physical network, which is known to be NP-hard. Recent studies focus on how to minimize the energy cost while maximizing the revenue of the physical network when the VN request arrives. However, after a period of time, due to the dramatic dynamics of the resources of the physical network, the previous solution may become less energy efficient. In this article, we study how to re-optimize the energy cost by leveraging the migration technique. In particular, we first give the problem model of virtual network migration. Then we design two energy aware virtual network migration algorithms called EA-VNM and EA-VNM-G. For EA-VNM, it answers the following key questions: when to perform migration, migrate which virtual nodes to where, and how to perform migration. Especially, for EA-VNM-G, it further reduces the high time complexity problem of EA-VNM by grouping the virtual nodes to be migrated with fewer conflicts. Extensive simulations show that EA-VNM significantly reduces the energy cost by up to 25 percent over the state-of-the-art algorithm while maintaining similar revenue and EA-VNM-G reduces the running time significantly.

关键词： Network as a service network virtualization virtual network migration energy cost label propagation

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NOMA-Based Collaborative Beam Hopping Frequency Allocation Mechanism for Future LEO Satellite Systems

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China Communications 2023年第6期20卷 321-338页

作者： Fei Zheng Zhao Pi Zou Zhou Miao Ye Hongbing Qiu Ministry of Education Key Laboratory of Cognitive Radio and Information Processing Guilin University of Electronic TechnologyGuilin 541004China State key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

Low Earth orbit(LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference(CCI). In the cluster area, a non-orthogonal multiple access(NOMA)-based collaborative beam hopping(NCBH) scheme is proposed to minimize the cell-edge user(CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user(CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user’s received power, transmission rate, and outage probability.

关键词： LEO satellite beam hopping NOMA resource allocation

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Minimum Spatial Sampling Method Under Spherical Test Zone in MIMO OTA Testing

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2024年第8期23卷 2466-2470页

作者： Hu, Zhenyun Zhang, Yuxiang Zhang, Jianhua Tian, Lei Wang, Heng Zhang, Xiang Yang, Xiaohang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China China Acad Informat & Commun Technol Beijing 100191 Peoples R China

In this letter, a novel 3-D test zone sampling method is proposed to realize efficient dynamic channel emulation in multiple-input-multiple-output (MIMO) over-the-air (OTA) testing. By characterizing the spatial correlation with Fourier expansion, this method can derive the minimum necessary number of test zone samples for high fidelity channel emulation. This approach significantly reduces the complexity associated with probe weight computation, which is essential for dynamic channel emulation. The simulation results indicate that compared with the sampling method with ${{\mathbf{0.1}}}$ wavelength interval, the proposed method reduces spatial samples of virtual antennas to ${{\mathbf{53.4}}\%}$, which is significant for MIMO OTA testing.

关键词： Multiple-input-multiple-output (MIMO) Nyquist sampling theorem over-the-air (OTA) testing test zone sampling Multiple-input-multiple-output (MIMO) Nyquist sampling theorem over-the-air (OTA) testing test zone sampling

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Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

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China Communications 2024年第1期21卷 131-147页

作者： Shuo Liu Pan Tang Jianhua Zhang Yue Yin Yu Tong Baobao Liu Guangyi Liu Liang Xia State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China China Mobile Research Institute Beijing 100053China

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)***,channel modeling is the foundation for designing efficient and robust VLC *** this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a *** on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical *** on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial ***,the simulated statistics of the proposed model are compared with the measured *** instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,***,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,***,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

关键词： channel characteristics channel measurement channel modeling 6G spatial lobe VLC

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