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Transitioning RingCT Accounts: From Classical to Post-Quantum Security

IEEE INTERNET OF THINGS JOURNAL 2025年第2期12卷 2090-2105页

作者： Duan, Junke Wang, Wei Wang, Licheng 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 classical protocol that enhances transaction privacy within blockchain technology. It is primarily utilized in anonymous cryptocurrencies such as Monero. In recent years, to counter the security threats posed by quantum computing to classical RingCT (C-RCT), several post-quantum RingCT (P-RCT) protocols were proposed. However, prior studies do not address the account transition from C-RCT to P-RCT, which is essential to ensure the quantum resistance and usability of user accounts following the upgrade from C-RCT to P-RCT. In this article, we introduce a RingCT account transition protocol (RAT), which allows users to migrate their accounts from the blockchain with C-RCT to that with P-RCT. The protocol consists of two cryptographic components: 1) a zero-knowledge proof scheme used to prove that two group generators correspond to the same witness and 2) a cross-cryptosystems commitment transition protocol. RAT is fully decentralized and does not require any trusted third parties. Additionally, the transition process does not disclose the account balance and maintains both atomicity and consistency. The security of our protocol relies on the cryptographic components within RingCT, without the need for additional security assumptions, such as a trusted setup. The experimental results demonstrate the effectiveness of our protocol in practice.

关键词： Protocols Security Blockchains Privacy Qubit Public key Internet of Things Blockchain commitment post-quantum ring confidential transactions (RingCT) transition

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Online Request Replication for Obtaining Fresh Information Under Pull Model

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IEEE INTERNET OF THINGS JOURNAL 2024年第16期11卷 27864-27875页

作者： Wang, Hongyan Sun, Qibo Li, Qing Ma, Xiao Wang, Shangguang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Peking Univ Sch Comp Sci Beijing 100871 Peoples R China

Age of Information (AoI) has gained widespread usage and emerged as a pivotal metric for assessing timeliness performance in information-update systems. Such systems often entail service requirements for rapidly obtaining requested data in real-time. For instance, in the financial market, users rely on up-to-date and low-latency information to make appropriate trading decisions to maximize profits within their financial budge. Much of the existing research on real-time services focuses on ensuring AoI or service-level latency, but there is a growing demand for joint optimization of these two metrics to accommodate a broader range of potential applications. Therefore, this article investigates the problem of minimizing AoI within the context of statistical latency guarantees. To tackle the critical challenges posed by the joint modeling of AoI and statistical latency, system uncertainty, as well as tradeoff between performance and user's budget, we employ a replication scheme to ensure both AoI and statistical service-level latency. To address the critical challenges posed by the unknown distribution in data updating processes and response times across providers, we formulate the AoI minimization problem with statistical latency constraints as a combinatorial multiarmed bandit problem utilizing the Lyapunov optimization theory. Subsequently, we propose an online learning-based request replication algorithm to address this problem. Our proposed algorithm achieves a cumulative regret of O(T root log (T)) compared to the genie-aided algorithm. Simulation results demonstrate the superior performance of the proposed algorithm against benchmarks.

关键词： Real-time systems Measurement Data models Delays Optimization Uncertainty Throughput Age of Information (AoI) Lyapunov multiarmed bandit (MAB) real-time data application request replication statistical service-level latency

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Learning-Based Deterministic Delay Performance Guarantee Strategy in RIS-Assisted Communication Networks

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IEEE INTERNET OF THINGS JOURNAL 2025年第2期12卷 1907-1921页

作者： Xu, Xiaodong Meng, Zhuo Zhang, Jingxuan Han, Shujun Wang, Bizhu Sun, Mengying Wang, Weidong Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Peng Cheng Lab Shenzhen 518066 Guangdong Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Univ Sci & Technol Beijing Beijing Engn & Technol Res Ctr Convergence Network Beijing 100083 Peoples R China Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China

In order to satisfy the requirements for service transformation and upgrading toward industrial digitization, networking, and intelligence, sixth generation-enabled industrial Internet of Things (IIoT) imposes new requirements on deterministic delay. However, the existing best-effort communication networks increase the uncertainty of transmission, making it difficult for users to ensure deterministic delay performance. In this article, we propose a deterministic delay guarantee strategy (DDGS) under reconfigurable intelligent surface (RIS)-assisted communication networks to ensure network performance in IIoT scenarios. In particular, we utilize stochastic network calculus (SNCs) to derive the probability that the delay falls within a specific time window, characterizing the probabilistic bounds of deterministic delay. Then, we explore the relationship between delay determinacy and wireless resources by jointly optimizing the transmit power, the channel blocklength allocation, and the phase-shift matrix at the RIS to maximize delay determinacy. Based on the interdependence of action choices among users and past experience, this article proposes a performance guarantee parameterized deep Q-network (PG-PDQN) algorithm to solve the complex problem containing a mixture of discrete and continuous action spaces. Simulation results show that the DDGS strategy significantly improves the delay determinacy compared to other strategies, and the PG-PDQN algorithm has good convergence, thus effectively improving the network performance.

关键词： Delays Industrial Internet of Things Communication networks Resource management Jitter 6G mobile communication Reliability Deep reinforcement learning (DRL) deterministic delay industrial Internet of Things (IIoT) performance guarantee strategy reconfigurable intelligence surface stochastic network calculus (SNCs)

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RIS-Enhanced Secure Transmission in MTC Networks With Finite Blocklength

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IEEE TRANSACTIONS ON COMMUNICATIONS 2023年第6期71卷 3513-3527页

作者： Lv, Suyu Xu, Xiaodong Han, Shujun Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China

In this paper, we propose a reconfigurable intelligent surface (RIS) assisted secure finite blocklength transmission framework in machine-type communications (MTC) networks, where the integration of millimeter-wave (mmWave) communication and non-orthogonal multiple access (NOMA) technology is considered to alleviate the problem of insufficient spectrum resources caused by massive MTC devices (MTCDs). For improving the ability of anti-eavesdropping, we aim to maximize the achievable sum secrecy capacity (SC) by jointly optimize the MTCDs' transmission power, RIS phase coefficient and receive beamforming design. To handle the nonconvexity of the proposed optimization problem, we decouple it into three sub-problems, where the first two are solved by successive convex approximation (SCA) method. A minimum mean squared error successive interference cancellation (MMSE-SIC) scheme is proposed to tackle the receive beamforming problem for uplink NOMA networks. Furthermore, an alternating optimization based joint power, phase, and beamforming allocation (AO-JPPBA) algorithm is developed to implement joint optimization. Simulation results show that: 1) the security performance of the proposed AO-JPPBA is improved by 612.26% than the baseline scheme;2) the proposed MMSE-SIC beamforming scheme is more effective in improving sum-SC of uplink NOMA networks;3) RIS's location has an obvious impact on sum-SC when considering eavesdroppers with strong wiretapping ability.

关键词： Machine-type communications finite blocklength millimeter-wave non-orthogonal multiple access reconfigurable intelligent surface secure transmission

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ScaIR: Scalable Intelligent Routing based on Distributed Graph Reinforcement Learning

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COMPUTER NETWORKS 2025年 257卷

作者： Zhang, Jing Guan, Jianfeng Liu, Kexian Hu, Yizhong Shen, Ao Ma, Yuyin Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China

Traditional routing typically relies on simpler performance metrics that can be derived directly through mathematical methods for decision-making, which often results in limited optimization outcomes. As future networks expand, along with the diversity of applications and traffic volume, the network environment grows increasingly complex. In contrast, Intelligent Routing (IR) that leverages machine learning methods can model more complex performance metrics, rendering it better suited to the intricate scenarios of future networks. The increasing complexity of networks also indicates that the workload associated with collecting routing information and executing decision calculations is growing exponentially. Compared to centralized IR, Distributed IR (DIR) distributes the computational load and interaction demands across multiple nodes, thereby offering enhanced scalability. However, DIR makes decisions based on local information, which limits global optimization. In this paper, we propose a novel Scalable Intelligent Routing based on Distributed Graph Reinforcement Learning, called ScaIR. ScaIR is a full y distributed multi-agent routing method. Each router is an independent agent based on local graph Reinforcement Learning (RL). Graph Neural Networks (GNN) are employed to extract global network characteristics which serve as input for RL, thereby enhancing global optimization. Especially, GNN here is also fully distributed. Each router has an independent sub-GNN determined by the adjacency relationships with its one-hop neighbors. Instead of entire network information and model parameters, each sub-GNN only iteratively interacts with its neighbors and computes a highly compressed Feature Vector (FV) representing the current network state, which greatly saves the computing and communication cost. We carried out extensive simulation experiments under multiple real network topologies of different scales. Simulation results show that ScaIR reduces forwarding time by mo

关键词： Large-scale network Intelligent routing Distributed GNN Reinforcement learning Multi-agent

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Semantic Base Enabled Image Transmission With Fine-Grained HARQ

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第4期24卷 3606-3622页

作者： Zheng, Yuan Wang, Fengyu Xu, Wenjun Zhang, Ping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples R China

Semantic communications (SemComs) which utilize the inherent meanings and relationships of data, have shown significant advantages for information transmission in recent years. In this paper, a novel semantic base (Seb) enabled SemCom framework is proposed, where Sebs, the basic units of fine-grained image semantics, are explicitly shared among transceivers to support image transmission. Specifically, first, to improve source coding efficiency, a Seb-based image codec is proposed, where semantics in each image patch are encoded with synchronized Sebs, that are generated from recent images. To ensure semantic consistency among the embeddings of Sebs, Gray coding is used to establish the projection, enhancing the framework's robustness against channel noise. The details of images are further refined by a residual codec for high-quality reconstructions. Second, to enhance transmission reliability with overhead as small as possible, a semantic-aware fine-grained hybrid automatic repeat request (SAFG-HARQ) is proposed, where only erroneous Sebs are retransmitted to precisely refine corrupted semantics using contextual correlations. Extensive simulations demonstrate that the proposed framework outperforms state-of-the-art works, where the image reconstruction quality is improved by 20% in learned perceptual image patch similarity (LPIPS), with a 60% reduction in transmission costs.

关键词： Semantics Image communication Image reconstruction Reliability Codecs Wireless communication Artificial neural networks Training Image coding Data models Semantic communications explicit semantic base image transmission semantic-aware HARQ

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Toward Copyright Integrity and Verifiability via Multi-Bit Watermarking for Intelligent Transportation Systems

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年

作者： Wang, Yihao Li, Lingxiao Tang, Yifan Zhang, Ru Liu, Jianyi Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Intelligent transportation systems (ITS) use advanced technologies such as artificial intelligence to significantly improve traffic flow management efficiency, and promote the intelligent development of the transportation industry. However, if the data in ITS is attacked, such as tampering or forgery, it will endanger public safety and cause social losses. Therefore, this paper proposes a watermarking that can verify the integrity of copyright in response to the needs of ITS, termed ITSmark. ITSmark focuses on functions such as extracting watermarks, verifying permission, and tracing tampered locations. The scheme uses the copyright information to build the multi-bit space and divides this space into multiple segments. These segments will be assigned to tokens. Thus, the next token is determined by its segment which contains the copyright. In this way, the obtained data contains the custom watermark. To ensure the authorization, key parameters are encrypted during copyright embedding to obtain cipher data. Only by possessing the correct cipher data and private key, can the user entirely extract the watermark. Experiments show that ITSmark surpasses baseline performances in data quality, extraction accuracy, and unforgeability. It also shows unique capabilities of permission verification and tampered location tracing, which ensures the security of extraction and the reliability of copyright verification. Furthermore, ITSmark can also customize the watermark embedding position and proportion according to user needs, making embedding more flexible.

关键词： Watermarking Data mining Security Ciphers Telecommunications Data integrity Encryption Copyright protection Vehicular ad hoc networks Transportation Intelligent transportation systems copyright watermark large language models GenAI

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Simultaneous Snow Mask Prediction and Single Image Desnowing with a Bidirectional Attention Transformer Network 7th

Simultaneous Snow Mask Prediction and Single Image Desnowing...

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7th Chinese Conference on Pattern Recognition and Computer Vision

作者： Zhang, Yonghong Yan, Danfeng BUPT State Key Lab Networking & Switching Technol Beijing Peoples R China BUPT Sch Comp Beijing Peoples R China

ISBN: (纸本)9789819786848;9789819786855

Snow's diverse shapes and sizes pose a significant challenge for single-image desnowing. Current methods typically rely on simple networks to predict the snow masks and subsequently remove snow from images accordingly. However, inaccurate predictions often result in incomplete snow removal. This paper introduces BAT-Net, a novel solution equipped with an image transformer encoder and dual transformer decoders. This architecture enables precise snow mask prediction and comprehensive single image desnowing simultaneously. The image encoder enhances and consolidates features from various layers using Scale Conversion Modules (SCM) and a Feature Aggregation Module (FAM). To ensure accurate snow mask prediction, the snow decoder mirrors the complete transformer structure of the background decoder. Within the background decoder, multiple Bidirectional Attention Modules (BAM) with integrated forward and reverse attention branches effectively leverage snow features and reverse snow features from the snow decoder, facilitating complete snow removal. Moreover, real-world desnowing datasets often contain fallen snow, complicating model training and validation. To address this challenge, we introduce the FallingSnow dataset, exclusively featuring scenes of falling snow. Experimental results across five diverse synthetic and real-world snow removal datasets demonstrate BAT-Net's significant advancements in addressing the challenges of snow mask prediction and single-image desnowing.

关键词： Single image desnowing Snow mask prediction Bidirectional attention

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Part-Aware Framework for Robust Object Tracking

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2023年 32卷 750-763页

作者： Li, Shengjie Zhao, Shuai Cheng, Bo Chen, Junliang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Guangxi Key Lab Cryptog & Informat Secur Guilin 541004 Peoples R China

The local parts of the target are vitally important for robust object tracking. Nevertheless, existing excellent context regression methods involving siamese networks and discrimination correlation filters mostly represent the target appearance from the holistic model, showing high sensitivity in scenarios with partial occlusion and drastic appearance changes. In this paper, we address this issue by proposing a novel part-aware framework based on context regression, which simultaneously considers the global and local parts of the target and fully exploits their relationship to be collaboratively aware of the target state online. To this end, the spatial-temporal measure among context regressors corresponding to multiple parts is designed to evaluate the tracking quality of each part regressor by solving the imbalance among global and local parts. The coarse target locations provided by part regressors are further aggregated by treating their measures as weights to refine the final target location. Furthermore, the divergence of multiple part regressors in each frame reveals the interference degree of background noise, which is quantified to control the proposed combination window functions in part regressors to adaptively filter redundant noise. Besides, the spatial-temporal information among part regressors is also leveraged to assist in accurately estimating the target scale. Extensive evaluations demonstrate that the proposed framework help many context regression trackers achieve performance improvements and perform favorably against state-of-the-art methods on the popular benchmarks: OTB, TC128, UAV, UAVDT, VOT, TrackingNet, GOT-10k, LaSOT.

关键词： Object tracking siamese network discrimina-tion correlation filter global and local parts

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From Earth to Space:A First Deployment of 5G Core Network on Satellite

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China Communications 2023年第4期20卷 315-325页

作者： Ruolin Xing Xiao Ma Ao Zhou Schahram Dustdar Shangguang Wang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Distributed Systems Group TU Wien1040 ViennaAustria

Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit *** new trend enables the paradigm shift of satelliteterrestrial integrated networks with global *** particular,the integration of 5G communication systems and satellites has the potential to restructure nextgeneration mobile *** leveraging the network function virtualization and network slicing,the satellite 5G core networks will facilitate the coordination and management of network functions in satellite-terrestrial integrated *** are the first to deploy a 5G core network on a real-world satellite to investigate its *** conducted experiments to validate the satellite 5G core network *** validated procedures include registration and session setup *** results show that the satellite 5G core network can function normally and generate correct signaling.

关键词： 5G core network satellite communications satellite Internet

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