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arXiv 2023年

作者： Zhou, Jiajun Xie, Chenxuan Gong, Shengbo Qian, Jiaxu Yu, Shanqing Xuan, Qi Yang, Xiaoniu Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Binjiang Institute of Artificial Intelligence Hangzhou310056 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou310023 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph neural networks (GNNs) and impeding their performance. Intriguingly, from the observation of heterophilous data, we notice that certain high-order information exhibits higher homophily, which motivates us to involve high-order information in node representation learning. However, common practices in GNNs to acquire high-order information mainly through increasing model depth and altering message-passing mechanisms, which, albeit effective to a certain extent, suffer from three shortcomings: 1) oversmoothing due to excessive model depth and propagation times;2) high-order information is not fully utilized;3) low computational efficiency. In this regard, we design a similarity-based path sampling strategy to capture smooth paths containing high-order homophily. Then we propose a lightweight model based on multi-layer perceptrons (MLP), named PathMLP, which can encode messages carried by paths via simple transformation and concatenation operations, and effectively learn node representations in heterophilous graphs through adaptive path aggregation. Extensive experiments demonstrate that our method outperforms baselines on 16 out of 20 datasets, underlining its effectiveness and superiority in alleviating the heterophily problem. In addition, our method is immune to over-smoothing and has high computational efficiency. The source code will be available in https://***/Graph4Sec-Team/PathMLP. Copyright © 2023, The Authors. All rights reserved.

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Analysis of blockchain protocol against static adversarial miners corrupted by long delay attackers

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science China(information sciences) 2020年第3期63卷 49-63页

作者： Quan YUAN Puwen WEI Keting JIA Haiyang XUE Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong University Department of Computer Science and Technology Tsinghua University State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences Data Assurance and Communication Security Research Center Chinese Academy of Sciences

Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused on rigorous analyses of the security of Nakamoto’s blockchain protocol in an asynchronous network where network delay must be considered. Wei, Yuan, and Zheng investigated the effect of a long delay attack against Nakamoto’s blockchain protocol. However, their proof only holds in the honest miner setting. In this study, we improve Wei, Yuan and Zheng’s result using a stronger model where the adversary can perform long delay attacks and corrupt a certain fraction of the miners. We propose a method to analyze the converge event and demonstrate that the properties of chain growth, common prefix, and chain quality still hold with reasonable parameters in our stronger model.

关键词： blockchain bitcoin random oracle delay consensus protocol

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Zhao, Yihan Duan, Xuting Zhou, Jianshan Zhang, Long School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9798350316308

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time. © 2023 IEEE.

关键词： Autonomous vehicles

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Byzantine-Robust Federated Learning Framework via a Server-Client Defense Mechanisms

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IEEE Internet of Things Journal 2025年

作者： Song, Anxiao Zhang, Tao Cheng, Ke Cao, Yang Zhu, Xinghui Shen, Yulong Xidian University School of Computer Science and Technology Xi’an China Shaanxi Key Laboratory of Network and System Security Shaanxi Xi’an710071 China Xidian University School of Computer Science and Technology Shaanxi Xi’an710071 China Xi’an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Shaanxi Xi’an710121 China Institute of Science Tokyo Department of Computer Science Tokyo Japan

Federated Learning (FL), a distributed machine learning (ML) framework, is susceptible to Byzantine attacks since the attacker can manipulate clients' local data or models to compromise the performance of the global model. There has been a wealth of defenses developed to mitigate the attacks by limiting the impact of malicious models. Nevertheless, the attacker can easily circumvent these approaches that rely solely on a single server-side defense, stemming from the high dimensionality of models and the variety of Byzantine attacks. Therefore, we propose Basalt, a Byzantine-robust federated learning framework with a server-client joint defense mechanism that enables multiple clients to train a global ML model under Byzantine attacks. On the client side, we design an efficient self-defense approach with model-level penalty loss that restricts local-benign divergence and decreases local-malicious correlation to prevent misclassification. On the server side, we present an efficient defense strategy based on the manifold and maximum clique, further strengthening the FL's resilience against Byzantine attacks. We provide theoretical guarantees for global model convergence in FL with Byzantine attacks. Our extensive experiments demonstrate that Basalt outperforms existing state-of-the-art works. Especially, it achieves nearly 100% accuracy for detecting malicious clients in nonindependent and nonidentically distributed (Non-IID) MNIST datasets under various Byzantine attacks. © 2014 IEEE.

关键词： Federated learning

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Secrecy Performance Analysis of RIS Assisted Ambient Backscatter communication Networks

arXiv

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arXiv 2024年

作者： Pei, Yingjie Yue, Xinwei Huang, Chongwen Lu, Zhiping The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China The Key Laboratory of Information and Communication Systems Ministry of Information Industry China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Hangzhou310027 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Beijing100191 China

Reconfigurable intelligent surface (RIS) and ambient backscatter communication (AmBC) have been envisioned as two promising technologies due to their high transmission reliability as well as energy-efficiency. This paper investigates the secrecy performance of RIS assisted AmBC networks. New closed-form and asymptotic expressions of secrecy outage probability for RIS-AmBC networks are derived by taking into account both imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) cases. On top of these, the secrecy diversity order of legitimate user is obtained in high signal-to-noise ratio region, which equals zero and is proportional to the number of RIS elements for ipSIC and pSIC, respectively. The secrecy throughput and energy efficiency are further surveyed to evaluate the secure effectiveness of RIS-AmBC networks. Numerical results are provided to verify the accuracy of theoretical analyses and manifest that: i) The secrecy outage behavior of RIS-AmBC networks exceeds that of conventional AmBC networks;ii) Due to the mutual interference between direct and backscattering links, the number of RIS elements has an optimal value to minimise the secrecy system outage probability;and iii) Secrecy throughput and energy efficiency are strongly influenced by the reflecting coefficient and eavesdropper’s wiretapping ability. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Distributionally robust optimization based chance-constrained energy management for hybrid energy powered cellular networks

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Digital communications and Networks 2023年第3期9卷 797-808页

作者： Pengfei Du Hongjiang Lei Imran Shafique Ansari Jianbo Du Xiaoli Chu The Engineering Research Center of Intelligent Air-ground Integrated Vehicle and Traffic Control Ministry of EducationXihua UniversityChengdu610039China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an710121China Electronic and Electrical Engineering University of SheffieldSheffieldS102TNUK

Energy harvesting has been recognized as a promising technique with which to effectively reduce carbon emis-sions and electricity expenses of base ***,renewable energy is inherently stochastic and inter-mittent,imposing formidable challenges on reliably satisfying users'time-varying wireless traffic *** addition,the probability distribution of the renewable energy or users’wireless traffic demand is not always fully known in *** this paper,we minimize the total energy cost of a hybrid-energy-powered cellular network by jointly optimizing the energy sharing among base stations,the battery charging and discharging rates,and the energy purchased from the grid under the constraint of a limited battery size at each base *** solving the formulated non-convex chance-constrained stochastic optimization problem,a new ambiguity set is built to characterize the uncertainties in the renewable energy and wireless traffic demands according to interval sets of the mean and *** this ambiguity set,the original optimization problem is transformed into a more tractable second-order cone programming problem by exploiting the distributionally robust optimization ***,a low-complexity distributionally robust chance-constrained energy management algo-rithm,which requires only interval sets of the mean and covariance of stochastic parameters,is *** results of extensive simulation are presented to demonstrate that the proposed algorithm outperforms existing methods in terms of the computational complexity,energy cost,and reliability.

关键词： Cellular networks Energy harvesting Energy management Chance-constrained Distributionally robust optimization

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Energy Consumption Minimization of Multi-UAV Assisted Mobile Edge Computing in SAGIN

Energy Consumption Minimization of Multi-UAV Assisted Mobile...

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IEEE International Conference on communications in China Workshops (ICCC)

作者： Qian Zhou Yuanyuan Yao Qi Liu Sai Huang Xinwei Yue Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Space-air-ground integrated networks (SAGIN) is one of the new network architectures in the 6th Generation Mobile communication technology (6G), which can provide higher speed and lower latency network access and coverage for ground user terminals. Under the premise of comprehensive connection, it provides solutions for service problems such as information acquisition, transmission, and processing. Given the remote geographical environment and the limited computing capability of users, SAGIN networks can provide reliable computing offload services within their coverage area by employing mobile edge computing servers on satellites and UAVs. In terms of the energy consumtion minimization problem, A Joint optimizing of offloading decision, task allocation, computing frequency and UAV deployment (JODFQ) algorithm is proposed, to decompose the original non-convex problem into three sub-problems that are iteratively solved alternately, while meeting the maximum tolerable latency of underlying tasks. Simulation results have verified the convergence and feasibility of the proposed algorithm. Compared with algorithms that use local-satellite, full-satellite and fixed UAV position schemes, the JODFQ algorithm effectively reduces the total system energy consumption. The research findings serve as a valuable reference for achieving low energy consumption and high efficiency SAGIN systems.

关键词： Space vehicles Energy consumption Multi-access edge computing Simulation Space-air-ground integrated networks Autonomous aerial vehicles Minimization Resource management Optimization Radio spectrum management

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Secure Beamforming Design for IRS-ISAC Systems with a Hardware-Efficient Hybrid Beamforming Architecture

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IEEE Transactions on Vehicular technology 2025年

作者： Xiong, Weijie Zhao, Zhenglan Lin, Jingran Xiao, Zhiling Li, Qiang University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China Tianfu Jiangxi Laboratory Sichuan Chengdu641419 China

In this paper, we employ a hardware-efficient hybrid beamforming (HB) architecture to achieve balanced performance in an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system. We consider a scenario where a multi-antenna, dual-function base station (BS) performs secure beamforming for a multi-antenna legitimate receiver while simultaneously detecting potential targets. Our objective is to maximize the communication secrecy gap by jointly optimizing the analog and digital beamformers, IRS reflection coefficients, and radar scaling factor, subject to constraints on beampattern similarity, total transmit power budget, and the constant modulus of both the analog beamformer and IRS reflection coefficients. This secrecy gap maximization problem is generally non-convex. To address this, we incorporate the exterior penalty method by adding the radar constraint as a penalty term in the objective function. We then propose an efficient approach based on the penalty dual decomposition (PDD) framework to solve the reformulated problem, featuring closed-form solutions at each step and guaranteeing convergence to a stationary point. Simulation results validate the effectiveness of the proposed algorithm and demonstrate the superiority of the IRS-ISAC system with HB architecture in balancing performance and hardware costs. © 1967-2012 IEEE.

关键词： Convex optimization

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C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期PP卷 PP页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Image-Text Matching Medical Report Generation Sample-graph Consistency Self-boosting framework

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Sensing With Random communication Signals

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IEEE Network 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China Nanjing University of Information Science and Technology School of Electronic and Information Engineering Nanjing210044 China Technical University of Berlin Faculty of Electrical Engineering and Computer Science Berlin10587 Germany Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security China Southeast University MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing211189 China

communication-centric Integrated Sensing and communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025 IEEE.

关键词： Mobile telecommunication systems

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