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中国邮电高校学报（英文版）
中国邮电高校学报（英文版）

郭更生

双月刊

1005-8885

jcupt@bupt.edu.cn

010-62282493

100876

北京邮电大学教一楼119室

中国邮电高校学报（英文版）/Journal The Journal of China Universities of Posts and TelecommunicationsCSCD北大核心EI
查看更多>>本刊是国内外公开发行的“以信息科学”为特色的学术性科技核心期刊。创刊于1994年，主要刊载通信与信息系统、信号与信息处理、计算机软件与理论、计算机应用技术、电磁场与微波技术、微电子学与固体电子学、控制理论与控制工程、管理科学与工程以及相关基础技术领域的学术论文、研究报告、综述、研究简报及学位论文等。
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    Black-box membership inference attacks based on shadow model

    Han ZhenZhou Wen'anHan XiaoxuanWu Jie...
    1-16页
    查看更多>>摘要：Membership inference attacks on machine learning models have drawn significant attention.While current research primarily utilizes shadow modeling techniques,which require knowledge of the target model and training data,practical scenarios involve black-box access to the target model with no available information.Limited training data further complicate the implementation of these attacks.In this paper,we experimentally compare common data enhancement schemes and propose a data synthesis framework based on the variational autoencoder generative adversarial network(VAE-GAN)to extend the training data for shadow models.Meanwhile,this paper proposes a shadow model training algorithm based on adversarial training to improve the shadow model's ability to mimic the predicted behavior of the target model when the target model's information is unknown.By conducting attack experiments on different models under the black-box access setting,this paper verifies the effectiveness of the VAE-GAN-based data synthesis framework for improving the accuracy of membership inference attack.Furthermore,we verify that the shadow model,trained by using the adversarial training approach,effectively improves the degree of mimicking the predicted behavior of the target model.Compared with existing research methods,the method proposed in this paper achieves a 2％improvement in attack accuracy and delivers better attack performance.
      原文链接:
    • 万方数据
    • 维普

    Personalized trajectory data perturbation algorithm based on quadtree indexing

    Liu KunJin JunhuiWang HuiShen Zihao...
    17-27页
    查看更多>>摘要：To solve the privacy leakage problem of truck trajectories in intelligent logistics,this paper proposes a quadtree-based personalized joint location perturbation(QPJLP)algorithm using location generalization and local differential privacy(LDP)techniques.Firstly,a flexible position encoding mechanism based on the spatial quadtree indexing is designed,and the length of the encoding can be adjusted freely according to data availability.Secondly,to meet the privacy needs of different locations of users,location categories are introduced to classify locations as sensitive and ordinary locations.Finally,the truck invokes the corresponding mechanism in the QPJLP algorithm to locally perturb the code according to the location category,allowing the protection of non-sensitive locations to be reduced without weakening the protection of sensitive locations,thereby improving data availability.Simulation experiments demonstrate that the proposed algorithm effectively meets the personalized trajectory privacy requirements while also exhibiting good performance in trajectory proportion estimation and top-k classification.
      原文链接:
    • 万方数据
    • 维普

    LRChain:data protection and sharing method of learning archives based on consortium blockchain

    Lan LinaGao YuhanShi RuishengWu Fenfen...
    28-42页
    查看更多>>摘要：Learning archives management in traditional systems faces challenges such as inadequate security,weak tamper resistance,and limited sharing capabilities.To address these issues,this paper proposes LRChain,a method based on consortium blockchain,for lifelong learning archives data protection and sharing.LRChain employs a combination of on-chain and off-chain cooperative storage using a consortium chain and inter planetary file system(IPFS)to enhance data security and availability.It also enables fine-grained verification of learning archives through selective disclosure principles,ensuring privacy protection of sensitive data.Furthermore,an attribute-based encryption(ABE)algorithm is utilized to establish authorized access control for learning archives,facilitating safe and trusted sharing.Experimental evaluations and security analyses demonstrate that this method exhibits decentralization,strong security,tamper resistance,and performs well,effectively meeting the requirements for secure sharing of learning archive data.
      原文链接:
    • 万方数据
    • 维普

    Improving link prediction models through a performance enhancement scheme:a study on semi-supervised learning and model soup

    Qi DonglinChen ShudongDu RongYu Yong...
    43-53页
    查看更多>>摘要：As an important method for knowledge graph(KG)complementation,link prediction has become a hot research topic in recent years.In this paper,a performance enhancement scheme for link prediction models based on the idea of semi-supervised learning and model soup is proposed,which effectively improves the model performance on several mainstream link prediction models with small changes to their architecture.This novel scheme consists of two main parts,one is predicting potential fact triples in the graph with semi-supervised learning strategies,the other is creatively combining semi-supervised learning and model soup to further improve the final model performance without adding significant computational overhead.Experiments validate the effectiveness of the scheme for a variety of link prediction models,especially on the dataset with dense relationships.In terms of CompGCN,the model with the best overall performance among the tested models improves its Hits@1 metric by 14.7％on the FB15K-237 dataset and 7.8％on the WN18RR dataset after using the enhancement scheme.Meanwhile,it is observed that the semi-supervised learning strategy in the augmentation scheme has a significant improvement for multi-class link prediction models,and the performance improvement brought by the introduction of the model soup is related to the specific tested models,as the performances of some models are improved while others remain largely unaffected.
      原文链接:
    • 万方数据
    • 维普

    Artificial rabbit optimization algorithm based on chaotic mapping and Levy flight improvement

    Wu JinSu ZhengdongGao YaqiongFeng Haoran...
    54-69页
    查看更多>>摘要：An artificial rabbit optimization(ARO)algorithm based on chaotic mapping and Levy flight improvement is proposed,which has the advantages of good initial population quality and fast convergence compared with the traditional ARO algorithm,called CLARO.CLARO is improved by applying three methods.Chaotic mapping is introduced,which can optimize the quality of the initial population of the algorithm.Add Levy flight in the exploration phase,which can avoid the algorithm from falling into a local optimum.The threshold of the energy factor is optimized,which can better balance exploration and exploitation.The efficiency of CLARO is tested on a set of 23 benchmark function sets by comparing it with ARO and different meta-heuristics algorithms.At last,the comparison experiments conclude that all three improvement strategies enhance the performance of ARO to some extent,with Levy flight providing the most significant improvement in ARO performance.The experimental results show that CLARO has better results and faster convergence compared to other algorithms,while successfully addressing the drawbacks of ARO and being able to face more challenging problems.
      原文链接:
    • 万方数据
    • 维普

    Power and rate adaption in wireless communication systems with energy harvesting-based on soft decision decoding

    Lei WeijiaYu ShunhongLiu Meiding
    70-82页
    查看更多>>摘要：In this paper,the online power control and rate adaptation for a wireless communication system with energy harvesting(EH)are investigated,in which soft decision decoding is adopted by the receiver.To efficiently utilize the harvested energy and maximize the actual achievable transmission rate under the constraints of the available channel codes and modulation schemes,the transmit power,code rate and modulation order are jointly optimized.The Lyapunov framework is used to transform the long-term optimization problem into a per time slot optimization problem.Since there is no theoretical formula for the error rate of soft decision decoding,the optimization problem cannot be solved analytically.A table to find the optimal modulation order and code rate under the different values of signal-to-noise ratio(SNR)is built first,and then a numerical algorithm to find the solution to the optimization problem is given.The feasibility and performance of the proposed algorithm are demonstrated by simulation.The simulation results show that compared with the algorithms to maximize the theoretical channel capacity,the proposed algorithm can achieve a higher actual transmission rate.
      原文链接:
    • 万方数据
    • 维普

    Dynamic coverage of mobile multi-target in sensor networks based on virtual force

    Huang QingdongWang MeiChen ChenHan Zhuang...
    83-94页
    查看更多>>摘要：A distributed self-control coverage method for mobile multi-target based on virtual force(MMTVF)is proposed to monitor dynamic targets using a mobile sensor network(MSN).The dynamic coverage method is introduced to maintain network connectivity and optimize the coverage of moving targets.The method consists of two parts,one is the virtual force model which is proposed for motion control,and the other is the whale optimization algorithm which is improved to optimize node positions and achieve a steady state quickly.The virtual resultant force stretches the network towards uncovered targets using its multi-target attractive force,maintains network connectivity during network stretching using its attractive force,and prevents node collisions while nodes are moving using its repulsive force.The operating mechanism of the multi-target attractive force and other forces is thoroughly analyzed.Adjustment criteria for the model in different application scenarios are also provided.The comparisons demonstrate MMTVF has significant advantages over other similar approaches.
      原文链接:
    • 万方数据
    • 维普

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      原文链接:
    • 万方数据