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Experimental demonstration of a quantum downstream access network in continuous variable quantum key distribution with a local local oscillator

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Photonics Research 2024年第6期12卷 1262-1273页

作者： DENGKE QI XIANGYU WANG ZHENGHUA LI JIAYU MA ZIYANG CHEN YUEMING LU SONG YU State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service(MoE) Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronicsand Center for Quantum Information TechnologyPeking UniversityBeijing 100871China

Quantum networks provide opportunities and challenges across a range of intellectual and technical frontiers,including quantum computation,communication,and *** traditional communication networks,quantum networks utilize quantum bits rather than classical bits to store and transmit *** key distribution(QKD)relying on the principles of quantum mechanics is a key component in quantum networks and enables two parties to produce a shared random secret key,thereby ensuring the security of data *** this work,we propose a cost-effective quantum downstream access network structure in which each user can get their corresponding key information through terminal *** on this structure,we demonstrate the first four-end-users quantum downstream access network in continuous variable QKD with a local local *** contrast to point-to-point continuous variable QKD,the network architecture reevaluates the security of each user and accounts for it accordingly,and each user has a lower tolerance for excess noise as the overall network expands with more ***,the feasibility of the experiment is based on the analysis of the theoretical model,noise analysis,and multiple techniques such as the particle filter and adaptive equalization algorithm used to suppress excess *** results show that each user can get a low level of excess noise and can achieve secret key rates of 546 kbps,535 kbps,522.5 kbps,and 512.5 kbps under a transmission distance of 10 km,respectively,with the finite-size block of 1×10~*** not only verifies the good performance but also provides the foundation for the future multi-user quantum downstream access networks.

关键词： quantum oscillator local

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Blockchain Storage Method Based on Erasure Code 8

Blockchain Storage Method Based on Erasure Code

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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Meng, Fanyao Li, Jin Gao, Jiaqi Liu, Junjie Ru, Junpeng Lu, Yueming School of Cyberspace Security Beijing University of Posts and Telecommunications Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications The State Key Laboratory of Information Photonics and Optical Communications Beijing China

ISBN: (纸本)9798350331035

Blockchain, as an emerging distributed database, effectively addresses the issue of centralized storage in IoT data, where storage capacity cannot match the explosive growth in devices and data scale, as well as the contradictions arising from centralized data management concerning data privacy and security concerns. To alleviate the problem of excessive pressure on single-point storage and ensure data security, a blockchain data storage method based on erasure codes is proposed. This method involves constructing mathematical functions that describe the data to split the original block data into multiple fragments and add redundant slices. These fragments are then encoded and stored in different locations using a circular hash space with the addition of virtual nodes to ensure load balancing among nodes and reduce situations where a single node stores too many encoded data blocks, effectively enhancing the storage space utilization efficiency of the distributed storage database. The blockchain storage method stores encoded data digest information such as storage location, creation time, and hashes, allowing for the tracing of the origin of encoded data blocks. In case of accidental loss or malicious tampering, this enables effective recovery and ensures the integrity and availability of data in the network. Experimental results indicate that compared to traditional blockchain approaches, this method effectively reduces the storage pressure on nodes and exhibits a certain degree of disaster recovery capability. © 2023 IEEE.

关键词： Blockchain Consistent Hashing Erasure Codes Internet of Things

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A&D Graph-Based Graph Neural Network Intrusion Detection for In-Vehicle Controller Area Network

A&D Graph-Based Graph Neural Network Intrusion Detection for...

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IEEE International Conference on communications in China (ICCC)

作者： Yaru He Jiaqi Gao Mingrui Fan Daoqi Han Yueming Lu Yaojun Qiao State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

The rapid advancement of the Internet of Vehicles (IoV) has significantly enhanced the diversity and intelligence of Electronic Control Units (ECUs) within the Controller Area Network (CAN) of vehicles. Implementing an effective Intrusion Detection System (IDS) is paramount for ensuring the security of the in-vehicle CAN. Traditional approaches in intrusion detection often rely on single-sample analysis, demanding extensive labeled data. To circumvent this limitation, a graph-based IDS that eliminates the necessity for single-sample labeling becomes imperative. Nonetheless, existing graph-based IDS models encounter the challenge of achieving high accuracy, especially for impersonation attacks. In this paper, we propose Arbitration&Data graph-based Graph Neural Networks (A&D-GNN) IDS to improve detection accuracy for in-vehicle CAN effectively. The proposed A&D-GNN IDS can significantly improve detection accuracy for impersonation attacks, which includes the Arbitration&Data (A&D) graph construction algorithm, representation learning, and intrusion detection. Based on the CAN message characteristics, the A&D directed attribute graph can extract comprehensive information, including information about both the arbitration field and the data field in the CAN message frame, notably, the data field is associated with the arbitration field. Therefore, the following Graph Neural Networks (GNN) with powerful representation capabilities can learn more precise graph-level representations. Lastly, a multi-classification layer is applied to perform intrusion detection. Experimental results on the public benchmark OTIDS dataset show that our proposed model is superior to other models with higher accuracy and an impressive accuracy of 99.92% for impersonation attacks.

关键词： Representation learning Accuracy Intrusion detection Impersonation attacks Data processing Graph neural networks Security

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Enhancing Algorithmic Fairness Through Counterfactual Data Augmentation

SSRN

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SSRN 2024年

作者： Xu, Yingchun Zhang, Xiaohang Xue, Haoyu Li, Zhengren School of Economics and Management Beijing University of Posts and Communications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing100876 China

In high-stakes AI fields such as criminal justice, loan applications, and graduate admissions, concerns about algorithmic discrimination are increasingly growing. This study proposes a novel counterfactual data augmentation method, termed Counterfactual Fairness Variational AutoEncoder (CFVAE), which integrates a Variational AutoEncoder and Causal model. The CFVAE is designed to enhance algorithmic fairness and transparency by generating both factual and counterfactual datasets. Moreover, the CFVAE framework introduces a novel counterfactual fairness loss function and utilizes cosine similarity to ensure the independence between exogenous variables and sensitive attributes, thereby guaranteeing the fairness quality of generated data. Extensive experiments have validated the effectiveness of our model, proving that it markedly improves the fairness of prediction models without substantial loss of data information while maintaining accuracy. © 2024, The Authors. All rights reserved.

关键词： Data accuracy

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Experimental Demonstration of 2D-Trellis Coded Modulation PAM8 for 50G PON Based on 10G-class O-Band DML 27

Experimental Demonstration of 2D-Trellis Coded Modulation PA...

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27th OptoElectronics and communications Conference/International Conference on Photonics in Switching and computing, OECC/PSC 2022

作者： Cui, Han Liu, Shuangyue Lu, Yueming Qiao, Yaojun School of Information and Communication Engineering State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China School of Cyberspace Security Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Ministry of Education Beijing100876 China

We present the first experimental demonstration of using 2D-TCM-PAM8 for a 50Gb/s PON system based on 10G-class O-band DML. Compared to PAM6, the receiver sensitivity of 2D-TCM-PAM8 is improved by 1.1 dB over 20-km tr... 详细信息

ISBN: (数字)9784885523366

ISBN: (纸本)9784885523366

关键词： Viterbi algorithm

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DW-MLSR: Unsupervised Deformable Medical Image Registration Based on Dual-Window Attention and Multi-Latent Space

SSRN

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SSRN 2024年

作者： Huang, YuXuan Yin, MengXiao Zhong, Cheng Li, ZhiPan Yang, Feng School of Computer and Electronic Information Guangxi University Nanning530004 China Guangxi Key Laboratory of Multimedia Communications Network Technology Guangxi University Guangxi Nanning530004 China Key Laboratory of Parallel Distributed and Intelligent Computing of Guangxi Universities and Colleges Nanning530004 China

Thanks to the emergence of transformers and Vision Transformer (VIT), attention mechanisms have also been applied to medical image registration. However, the current attention mechanisms in medical image registration suffer from incomplete information interaction. Common unsupervised registration methods may be constrained by the imperfect medical image data with uncertainty and noise, leading to unstable registration results susceptible to *** address these evident drawbacks, this paper proposes a novel medical image registration method, namely, Registration Based on Dual-Window Attention and Multi-Latent Space(DW-MLSR). The Dual-Window attention mechanism introduced in this paper enables the model to comprehensively focus on crucial local regions in the image, thereby improving registration accuracy and robustness. Meanwhile, MLS, employed as a data augmentation method, enhances the model's generalization ability and robustness by learning latent image representations, providing richer image *** results demonstrate the superiority of the proposed medical image registration method over mainstream registration models. Comparative experiments indicate that our approach holds significant application potential in the field of medical image registration. © 2024, The Authors. All rights reserved.

关键词： Image enhancement

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Enhancing IoT Flow Anomaly Detection with Differential Optimal Feature Subspace

Enhancing IoT Flow Anomaly Detection with Differential Optim...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Weidong Shi Mingrui Fan Jiaqi Gao Jiahao Qi Daoqi Han Yueming Lu Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education School of Cyberspace Security The State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

With the continuous expansion of network scale and increasing complexity, the application of the Internet of Things (IoT) is becoming more extensive. However, it is also vulnerable to various abnormal attacks, making security problems increasingly significant. Typically, traffic data dimensions are relatively large, and selecting features effectively is a key research issue. Addressing the aforementioned problems, this paper analyzes network traffic data and proposes a method(DOFS) to select the optimal feature subspace for different types of attacks, and verifies its effectiveness by comparative experiments. Then the T-S feature selection algorithm is improved, and DOFS is applied to the improved T-S feature selection algorithm, and the usability of the method is verified by experiments. By obtaining feature importance scores, the best feature subspace is selected for each type of traffic category. The method is verified using the network flow dataset CIC2018 and a real-world flow dataset. Experimental evaluations on diverse datasets demonstrate that the proposed method outperforms existing feature selection algorithms under different evaluation metrics, while exhibiting efficient time over-head and strong generalization ability. The results highlight the effectiveness and practicality of the proposed approach in IoT flow anomaly detection.

关键词：

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Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

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Engineering 2022年第1期8卷 60-73页

作者： Ping Zhang Wenjun Xu Hui Gao Kai Niu Xiaodong Xu Xiaoqi Qin Caixia Yuan Zhijin Qin Haitao Zhao Jibo Wei Fangwei Zhang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Peng Cheng Laboratory Shenzhen 518066China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China The School of Electronic Engineering and Computer Science Queen Mary University of LondonLondon E14NSUK College of Electronic Science and Technology National University of Defense TechnologyChangsha 410073China School of Humanities Beijing University of Posts and TelecommunicationsBeijing 100876China

The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G *** hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological *** this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G *** particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network *** the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information *** proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in *** features a lower bandwidth requirement,less redundancy,and more accurate intent *** also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.

关键词： 6G Semantic information Semantic communication Intelligent communication

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RoSAS: Deep Semi-supervised Anomaly Detection with Contamination-resilient Continuous Supervision

arXiv

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arXiv 2023年

作者： Xu, Hongzuo Wang, Yijie Pang, Guansong Jian, Songlei Liu, Ning Wang, Yongjun National Key Laboratory of Parallel and Distributed Computing China College of Computer National University of Defense Technology Hunan Changsha410073 China School of Computing and Information Systems Singapore Management University Singapore178902 Singapore College of Information and Communications National University of Defense Technology Hubei Wuhan430010 China

Semi-supervised anomaly detection methods leverage a few anomaly examples to yield drastically improved performance compared to unsupervised models. However, they still suffer from two limitations: 1) unlabeled anomalies (i.e., anomaly contamination) may mislead the learning process when all the unlabeled data are employed as inliers for model training;2) only discrete supervision information (such as binary or ordinal data labels) is exploited, which leads to suboptimal learning of anomaly scores that essentially take on a continuous distribution. Therefore, this paper proposes a novel semi-supervised anomaly detection method, which devises contamination-resilient continuous supervisory signals. Specifically, we propose a mass interpolation method to diffuse the abnormality of labeled anomalies, thereby creating new data samples labeled with continuous abnormal degrees. Meanwhile, the contaminated area can be covered by new data samples generated via combinations of data with correct labels. A feature learning-based objective is added to serve as an optimization constraint to regularize the network and further enhance the robustness w.r.t. anomaly contamination. Extensive experiments on 11 real-world datasets show that our approach significantly outperforms state-of-the-art competitors by 20%-30% in AUC-PR and obtains more robust and superior performance in settings with different anomaly contamination levels and varying numbers of labeled anomalies. The source code is available at https://***/xuhongzuo/rosas/. © 2023, CC BY.

关键词： Contamination

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EML-Based IM/DD Transmission over Dispersion-Uncompensated Links Using Low-Complexity Optimized Detection

EML-Based IM/DD Transmission over Dispersion-Uncompensated L...

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2021 Asia communications and Photonics Conference, ACP 2021

作者： Liu, Shuangyue Cui, Han Tang, Xizi Lu, Yueming Qiao, Yaojun State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing100876 China

We experimentally demonstrate an EML-based 40-Gbit/s OOK IM/DD transmission over 120-km SSMF using a low-complexity optimized detection algorithm, which requires no multiplication during the update of survival path, s... 详细信息

ISBN: (纸本)9781957171005

关键词： Chromatic dispersion

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