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5th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2023

作者： Zhang, Jiahui Yu, Le Zhang, Feng State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China China Mobile Communications Corporation Beijing100053 China

ISBN: (纸本)9781643684840

Industrial control systems play a crucial role in society, and ensuring the security of industrial control systems has become an important and challenging task. Intrusion detection is an important defense mechanism for protecting these systems. However, in existing industrial control intrusion detection techniques, especially those based on deep learning, a large number of training samples are usually required, and real-world samples often exhibit data imbalance, which can affect the training effectiveness. In this paper, a network intrusion detection model based on domain adaptation is proposed, which is a sample-discriminating adversarial domain adaptation model that can classify all samples of the target domain in a universal domain adaptation scenario. © 2024 The Authors.

关键词： Intrusion detection

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Explain-Analyze-Generate: A Sequential Multi-Agent Collaboration Method for Complex Reasoning 31

Explain-Analyze-Generate: A Sequential Multi-Agent Collabora...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Gu, Wenyuan Han, Jiale Wang, Haowen Li, Xiang Cheng, Bo State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China Hong Kong University of Science and Technology Hong Kong School of Computer Science and Technology Anhui University China

ISBN: (纸本)9798891761964

Exploring effective collaboration among multiple large language models (LLMs) represents an active research direction, with multiagent debate (MAD) emerging as a popular approach. MAD involves LLMs independently generating responses and refining their own responses by incorporating feedback from other agents in a debate manner. However, empirical experiments reveal the suboptimal performance of MAD in complex reasoning scenarios. We attribute this to the potential misleading caused by peer agents with limited individual capabilities. To address this, we propose a novel sequential collaboration framework named Explain-Analyze-Generate (EAG). By decomposing complex tasks into essential subtasks and employing a pipeline approach, EAG enable agents provide constructive assistance to peers, ultimately yielding higher performance. We conduct experiments on the comprehensive complex language reasoning benchmark: BIG-Bench-Hard (BBH). Our method achieves the highest performance on 19 out of 23 tasks, with an average improvement of 8% across all tasks, and incurs lower costs compared to MAD, demonstrating its effectiveness and efficiency. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Energy Consumption Minimization for NOMA-Based Secure UAV-MEC Network

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China Communications 2025年第3期22卷 202-216页

作者： Zhang Hao Huang Yuzhen Zhang Zhi Lu Xingbo School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China The Academy of Military Sciences of PLA Beijing 100091China

Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage ***,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless *** paper considers a UAV-MEC secure network based on NOMA technology,which aims to minimize the UAV energy *** achieve the purpose while meeting the security and users’latency requirements,we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network *** that the original problem is non-convex and multivariate coupled,we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA)and block coordinate descent(BCD).The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.

关键词： MEC NOMA resource optimization secure transmission trajectory optimization UAV

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An Experimental Analysis of Channel Similarity in the UMa Scenario for 6G FR3 Communications 7

An Experimental Analysis of Channel Similarity in the UMa Sc...

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7th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2024

作者： Chen, Ke Tang, Pan Jiang, Tao Xu, Huixin Nie, Gaofeng Tian, Lei Zhang, Jianhua Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China China Mobile Research Institution Beijing100053 China

ISBN: (纸本)9798350384437

In the development of the sixth generation (6G) wireless communication, FR3 (7-24 GHz) has gradually become the focus band due to its advantages of wide coverage and high capacity. However, the span of the FR3 is large, and the channel characteristics within the band have not been fully studied. In this paper, we conduct channel measurements campaigns in Urban Macro (UMa) scenario at FR3 using the channel sounder, and analyse the channel similarity. Firstly, channel measurements are conducted in UMa scenario at 11-15 GHz using a time domain channel measurement platform, with three receiver antennas of different beamwidths. Subsequently, the channel impulse response (CIR) similarity in frequency domain and beam domain is analyzed using pearson correlation coefficient (PCC) and temporal power delay distribution correlation coefficient (TPCC) as metrics. Finally, it is found that as the channel frequency interval increases, there is a trend of decreasing channel similarity. Additionally, great differences in antenna beamwidths also lead to lower channel similarity. © 2024 IEEE.

关键词： Impulse response

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SecureXGB: A Secure and Efficient Multi-party Protocol for Vertical Federated XGBoost

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Proceedings of the ACM on Management of Data 2025年第1期3卷 1-26页

作者： Zongda Han Xiang Cheng Wenhong Zhao Jiaxin Fu Zhaofeng He Sen Su State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

Extreme Gradient Boosting (XGBoost) demonstrates excellent performance in practice and is widely used in both industry and academic research. This extensive application has led to a growing interest in employing multi-party data to develop more robust XGBoost models. In response to increasing concerns about privacy leakage, secure vertical federated XGBoost is proposed. It employs secure multi-party computation techniques, such as secret sharing (SS), to allow multiple parties holding vertically partitioned data, i.e., disjoint features on the same samples, to collaborate in constructing an XGBoost model. However, the running efficiency is the primary obstacle to the practical application of existing protocols, especially in multi-party settings. The reason is that these protocols not only require the execution of data-oblivious computations to protect intermediate results, leading to high computational complexity, but also involve a large number of SS-based non-linear operations with high overheads, e.g., division operations in gain score calculation and comparison operations in best split selection. To this end, we present a secure and efficient multi-party protocol for vertical federated XGBoost, called SecureXGB, which can perform the collaborative training of an XGBoost model in an SS-friendly manner. In SecureXGB, we first propose a parallelizable multi-party permutation method, which can secretly and efficiently permute all samples before model training to reduce the reliance on data-oblivious computations. Then, we design a linear gain score that can be evaluated without involving division operations and has equivalent utility to the original gain score. Finally, we develop a synchronous best split selection method to secretly identify the best split with the maximum gain score using a minimal number of comparison operations. Experimental results demonstrate that SecureXGB can achieve better training efficiency than state-of-the-art protocols without the los

关键词： gradient boosting tree privacy-preserving machine learning vertical federated learning

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Global Patch-wise Attention is Masterful Facilitator for Masked Image Modeling 24

Global Patch-wise Attention is Masterful Facilitator for Mas...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Xi, Gongli Tian, Ye Yang, Mengyu Zhang, Lanshan Que, Xirong Wang, Wendong State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798400706868

Masked image modeling (MIM), as a self-supervised learning paradigm in computer vision, has gained widespread attention among researchers. MIM operates by training the model to predict masked patches of the image. Given the sparse nature of image semantics, it is imperative to devise a masking strategy that steers the model towards reconstructing high-semantic regions. However, conventional mask strategies often miss these high-semantic regions or lack alignment with the masks and semantics. To solve this, we propose the Global Patch-wise Attention (GPA) framework, a transferable and efficient framework for MIM pre-training. We observe that the attention between patches can be the metric of identifying high-semantic regions, which can guide the model to learn more effective representations. Therefore, we firstly define the global patch-wise attention via vision transformer blocks. Then we design the soft-to-hard mask generation to guide the model gradually focusing on high semantic regions identified by GPA (GPA as a teacher). Finally, we design an extra task to predict GPA (GPA as a feature). Experiments conducted under various settings demonstrate that our proposed GPA framework enables MIM to learn better representations, which benefit the model across a wide range of downstream tasks. Furthermore, our GPA framework can be easily and effectively transferred to various MIM architectures. © 2024 ACM.

关键词： Self-supervised learning

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Relay Node Placement with Base Stations in Wireless Sensor Networks Fault-Tolerant

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Chinese Journal of Electronics 2025年第4期23卷 794-800页

作者： Zhipeng Gao Kan Chen Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

It has been proposed to deploy relay nodes for the sake of prolonging Wireless sensor networks (WSN) lifetime, such that sensors transmit the sensed data to them which in turn delivers the data to base stations. For survivability requirements, relay placements which considers fault tolerant ability have been noticed and studied. While related works are limited or most existing works don't take factors such as fault tolerance, or base stations into account comprehensively in two tired WSN. We focus on fault tolerant relay node placement in two-tiered heterogeneous WSN with base stations. As far as we know, fault tolerance contains two fundamental aspects, for one is multi-coverage and the second is multi-path. It is a NP-hard problem and figure out an approximation, whose approximation ratio is enhanced to be $(18+\epsilon)$ . While a sub-problem approximation is also described as supplementary. Experimental results verify that the number of relay nodes deployed by our algorithm is somewhat superior to existed relay node placement solutions.

关键词： Measurement Fault tolerance Wireless sensor networks Base stations NP-hard problem Fault tolerant systems Approximation algorithms Sensors Relays

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Electromagneticwave property inspired radio environment knowledge construction and artificial intelligence based verification for6G digital twin channel

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Frontiers of Information technology & Electronic Engineering 2025年第2期26卷 260-277页

作者： Jialin WANG Jianhua ZHANG Yutong SUN Yuxiang ZHANG Tao JIANG Liang XIA State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China China Mobile Research Institute Beijing 100053China

As the underlying foundation of a digital twin network(DTN),digital twin channel(DTC)can accurately depict the electromagnetic wave propagation in the air interface to support the DTN-based 6G wireless *** electromagnetic wave propagation is affected by the environment,constructing the relationship between the environment and radio wave propagation is the key to implementing *** the existing methods,the environmental information inputted into the neural network has many dimensions,and the correlation between the environment and the channel is unclear,resulting in a highly complex relationship construction *** solve this issue,we propose a unified construction method of radio environment knowledge(REK)inspired by the electromagnetic wave property to quantify the propagation contribution based on easily obtainable location *** effective scatterer determination scheme based on random geometry is proposed which reduces redundancy by 90%,87%,and 81%in scenarios with complete openness,impending blockage,and complete blockage,*** also conduct a path loss prediction task based on a lightweight convolutional neural network(CNN)employing a simple two-layer convolutional structure to validate REK’s *** results show that only 4 ms of testing time is needed with a prediction error of 0.3,effectively reducing the network complexity.

关键词： Digital twin channel Radio environment knowledge(REK)pool Wireless channel Environmental information Interpretable REK construction Artificial intelligence based knowledge verification

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Probe Selection Method based on Switch Matrix for 5G Massive MIMO Base Station OTA Testing

Probe Selection Method based on Switch Matrix for 5G Massive...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Zhao, Jie Ma, Nan Liu, Baoling Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Beijing Key Laboratory of Wireless Communication Test Technology Beijing100102 China

ISBN: (纸本)9798350345384

The sectored multi-probe anechoic chamber method (MPAC) is considered to be the most promising method for 5G massive multiple-input multiple-output (MIMO) base station (BS) over-the-air (OTA) testing. In this case, the number of channel simulators and probes used in the testing system is increasing to reproduce the wireless propagation channel in a laboratory environment, which leads to a significant increase in the cost of the testing system and the complexity of probe selection. In this paper, a group-based switch matrix and corresponding probe selection algorithm are proposed. The simulation results indicate that the proposed method can accurately reconstruct the channel environment around the device-under-test (DUT) with fewer probes and lower computational complexity. Additionally, the impact of different probe configurations on the accuracy of channel emulation is also discussed. © 2023 IEEE.

关键词： Probes

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Turn on the Right Track: Weakly Supervised Video Moment Retrieval with Self-Improving Query Reconstruction 26

Turn on the Right Track: Weakly Supervised Video Moment Retr...

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Zhong, Yiming Sun, Haifeng Hao, Jiachang Wang, Jing Zhou, Cheng Qi, Qi Wang, Jingyu Liao, Jianxin State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China China Mobile Research Institute China

ISBN: (纸本)9781643684369

Existing weakly-supervised temporal sentence grounding methods typically regard query reconstruction as the pretext task in place of the absent temporal supervision. However, their approaches suffer from two flaws, i.e. insignificant reconstruction and discrepancy in alignment. Insignificant reconstruction indicates the randomly masked words may not be discriminative enough to distinguish the target event from unrelated events in the video. Discrepancy in alignment indicates the incorrect partial alignment built by query reconstruction task. The flaws undermine the reliability of current reconstruction-based methods. To this end, we propose a novel Self-improving Query ReconstrucTion (SQRT) framework for weakly-supervised temporal sentence grounding. To deal with insignificant reconstruction, we devise a key words mining strategy to determine the important words for language grounding. To attain better moment-query alignment, we introduce inter-sample contrast to tackle the partial alignment built by query reconstruction. The self-improving framework utilizes query reconstruction for language grounding and alleviates the discrepancy in alignment, thus turning on the right track. Experiments on two popular datasets show that SQRT achieves state-of-the-art performance on Charades-STA and comparable performance to the state-of-the-art on ActivityNet Captions. © 2023 The Authors.

关键词： Alignment

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