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SensFL:Privacy-Preserving Vertical Federated Learning with Sensitive Regularization

Computer Modeling in Engineering & Sciences 2025年第1期142卷 385-404页

作者： Chongzhen Zhang Zhichen Liu Xiangrui Xu Fuqiang Hu Jiao Dai baigen cai Wei Wang School of Automation and Intelligence Beijing Jiaotong UniversityBeijing100044China Shuohuang Railway Development Co. Ltd.National Energy GroupCangzhou062350China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation School of Computer Science and TechnologyBeijing Jiaotong UniversityBeijing100044China

In the realm of Intelligent Railway Transportation Systems,effective multi-party collaboration is crucial due to concerns over privacy and data *** Federated Learning(VFL)has emerged as a promising approach to facilitate such collaboration,allowing diverse entities to collectively enhance machine learning models without the need to share sensitive training ***,existing works have highlighted VFL’s susceptibility to privacy inference attacks,where an honest but curious server could potentially reconstruct a client’s raw data from embeddings uploaded by the *** vulnerability poses a significant threat to VFL-based intelligent railway transportation *** this paper,we introduce SensFL,a novel privacy-enhancing method to against privacy inference attacks in ***,SensFL integrates regularization of the sensitivity of embeddings to the original data into the model training process,effectively limiting the information contained in shared *** reducing the sensitivity of embeddings to the original data,SensFL can effectively resist reverse privacy attacks and prevent the reconstruction of the original data from the *** experiments were conducted on four distinct datasets and three different models to demonstrate the efficacy of *** results show that SensFL can effectively mitigate privacy inference attacks while maintaining the accuracy of the primary learning *** results underscore SensFL’s potential to advance privacy protection technologies within VFL-based intelligent railway systems,addressing critical security concerns in collaborative learning environments.

关键词： Vertical federated learning privacy defenses

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Survey of Performance Evaluation Standardization and Research Methods on GNSS-Based Localization for Railways

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Chinese Journal of Electronics 2020年第1期29卷 22-33页

作者： cai baigen WU Boqian LU Debiao Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transportation School of Electronic and Information Engineering Beijing Jiaotong University

Global navigation satellite systems(GNSS) has been regarded as a key technology for train localization in the future, as GNSS-based localization can reduce the deployment of wayside equipment, and offer a high-accuracy determination in a cost effective ***, the standardization of GNSS-based localization performance characteristics has not been done in *** can restrict the development of GNSS for safety related applications, which need critical requirement for the. The main objective of this paper is to provide a survey of research dealing with performance evaluation standardization. Train localization technique and performance requirement in Chinese train control system(CTCS), GNSS performance characteristics suggested in standards and guidelines, characteristics of accuracy/integrity/reliability/availability/safety for GNSS-based train localization and related evaluation approaches are presented. Some issues in GNSS-based train localization are highlighted based on the survey.

关键词： Railway GNSS Performance evaluation Train localization Safety

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Virtual Coupling Trains Based on Multi-Agent System Under Communication Delay

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Chinese Journal of Electronics 2024年第6期33卷 1545-1554页

作者： Guodong QIN Xiangxi MENG Tao WEN baigen cai School of Automation and Intelligence Beijing Jiaotong University The Institute of System Research China Industrial Control Systems Cyber Emergency Response Team

With the rapid development of railway transportation, virtual coupling(VC) has become a popular research topic. VC can greatly reduce tracking distance and increase the line capacity. Under VC control, the train formation control not only considers the behavior and speed adjustment strategy of the leader train but also the communication delays between trains. The quality of data communication between trains is an important aspect of train tracking control. We consider a virtually coupled train set(VCTS) as a multi-agent system. The Luenberger observer is introduced to estimate the real-time state of the train, based on the estimation, the train control consistency protocol is designed to account for communication delays. The stability of the error system is proven by constructing a Lyapunov function. The consistency of the coordinated train control is verified through simulation.

关键词： Couplings Protocols Transportation Observers Stability analysis Real-time systems Formation control Delays Multi-agent systems Lyapunov methods

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Dependability analysis of the data communication system in train control system

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Science China(Technological Sciences) 2009年第9期52卷 2605-2618页

作者： XU TianHua TANG Tao GAO ChunHai cai baigen State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China

Communication based train control (CBTC) system is based on mobile communication and overcomes fixed blocks in order to increase track utilization and train safety. The data communication system (DCS) between trains and wayside equipment is a crucial factor for the safe and efficient operation of CBTC system. The dependability under various transmission conditions needs to be modeled and evaluated. In this paper,a stochastic reward net (SRN) model for DCS based IEEE 802.11 standard was developed,which captures all relevant failure and failure recovery behavior system aspects in a concise way. We compared the reliability,availability for DCS with and without access point (AP) and antenna redundant configuration. We also quantitatively evaluated and compared the frame loss probability for three DCS configurations with different train velocities and train numbers in one radio cell. Fixed-point iteration was adopted to simplify the analysis. Numerical results showed the significant improvement of the reliability,availability and the frame loss probability index for the full redundant configuration.

关键词： dependability analysis data communication system (DCS) stochastic reward net (SRN) communication based train control (CBTC)

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A Novel Integrated Path Planning Algorithm for Warehouse AGVs

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Chinese Journal of Electronics 2021年第2期30卷 331-338页

作者： WEN Tao YANG Daichuan LIU Weifeng WEN Chenglin cai baigen School of Electronic and Information Engineering Beijing Jiaotong University School of Automation Hangzhou Dianzi University

We propose an integrated path planning method for multiple automated guided vehicles performing logistics delivery within a real-world warehouse environment considering obstacles. By applying it on each vehicle,this proposed method enables the vehicle the vehicles have the capabilities for autonomous path planning. The path planning consists of three parts, K-means algorithm based task points clustering, genetic algorithm based task points ordering, and the probabilistic road map based best path search. Vehicle conflict resolution is depending on implementing the probabilistic road map construction considering the realistic map with *** simulations result validate that the clustering and ordering are necessary for the path planning, both the path planning time and the Automated guided vehicles(AGVs)running time can be dramatically reduced.

关键词： path planning time vehicle conflict resolution real-world warehouse environment probabilistic road map construction path planning collision avoidance integrated path planning method mobile robots autonomous path planning genetic algorithm algorithm based task points path search vehicles running time novel integrated path planning algorithm logistics genetic algorithms automatic guided vehicles multiple automated guided vehicles logistics delivery

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Variable Selection in Logistic Regression Model

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Chinese Journal of Electronics 2015年第4期24卷 813-817页

作者： ZHANG Shangli ZHANG Lili QIU Kuanmin LU Ying cai baigen School of Science Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Department of Statistic Chonnam National University

Variable selection is one of the most important problems in pattern recognition. In linear regression model, there are many methods can solve this problem,such as Least absolute shrinkage and selection operator(LASSO) and many improved LASSO methods, but there are few variable selection methods in generalized linear models. We study the variable selection problem in logistic regression model. We propose a new variable selection method – the logistic elastic net, prove that it has grouping effect which means that the strongly correlated predictors tend to be in or out of the model together. The logistic elastic net is particularly useful when the number of predictors(p) is much bigger than the number of observations(n). By contrast, the LASSO is not a very satisfactory variable selection method in the case when p is more larger than n. The advantage and effectiveness of this method are demonstrated by real leukemia data and a simulation study.

关键词： Variable selection LASSO Linear regression model Logistic elastic net Logistic regression model

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Study on key technologies of GNSS-based train state perception for traincentric railway signaling

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High-Speed Railway 2023年第1期1卷 47-55页

作者： baigen cai Jingnan Liu Xurong Dong Jiang Liu School of Computer and Information Technology Bejing Jiaotong UniversityBeijing 100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing 100044China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China GNSS Research Center Wuhan UniversityWuhan 430079China Space Engineering University Beijing 101416China

The application of Global Navigation Satellite Systems(GNSSs)in the intelligent railway systems is rapidly developing all over the *** the GNSs-based train positioning and moving state perception,the autonomy and flexibility of a novel train control system can be greatly enhanced over the existing solutions relying on the track-side *** the safety critical features of the railway signaling applications,the GNSS stand-alone mode may not be sufficient to satisfy the practical *** this paper,the key technologies for applying GNSS in novel train-centric railway signaling systems are investigated,including the multi-sensor data fusion,Virtual Balise(VB)capturing and messaging,train integrity monitoring and system performance *** to the practical characteristics of the novel train control system under the moving block mode,the details of the key technologies are *** demonstration results of a novel train control system using the presented technologies under the practical railway operation conditions are presented to illustrate the achievable performance feature of autonomous train state perception using BeiDou Navigation Satellite System(BDS)and related *** reveals the great potentials of these key technologies in the next generation train control system and other GNSS-based railway implementations.

关键词： Railway signaling Train control Global Navigation Satellite System Sensor data fusion Virtual Balise Train integrity Performance evaluation

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Virtual sample generation for model-based prognostics and health management of on-board high-speed train control system

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High-Speed Railway 2023年第3期1卷 153-161页

作者： Jiang Liu baigen cair Jinlan Wang Jian Wang School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China Frontiers Science Center for Smart High-speed Railway System Bejing Jiaotong UniversityBeijing 100044China School of Computer and Information Technology Bejing Jiaotong UniversityBejing 100044China Guangzhou Railway Polytechnic Guangzhou 511300China

In view of class imbalance in data-driven modeling for Prognostics and Health Management(PHM),existing classification methods may fail in generating effective fault prediction models for the on-board high-speed train control equipment.A virtual sample generation solution based on Generative Adversarial Network(GAN)is proposed to overcome this *** at augmenting the sample classes with the imbalanced data problem,the GAN-based virtual sample generation strategy is embedded into the establishment of fault prediction *** the PHM framework of the on-board train control system,the virtual sample generation principle and the detailed procedures are *** the enhanced class-balancing mechanism and the designed sample augmentation logic,the PHM scheme of the on-board train control equipment has powerful data condition adaptability and can effectively predict the fault probability and life cycle *** data from a specific type of on-board train control system is employed for the validation of the presented *** comparative results indicate that GAN-based sample augmentation is capable of achieving a desirable sample balancing level and enhancing the performance of correspondingly derived fault prediction models for the Condition-based Maintenance(CBM)operations.

关键词： High-speed railway Prognostics and health management Train control Virtual sample Generative adversarial network

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Privacy-Preserving Large-Scale AI Models for Intelligent Railway Transportation Systems:Hierarchical Poisoning Attacks and Defenses in Federated Learning

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Computer Modeling in Engineering & Sciences 2024年第11期141卷 1305-1325页

作者： Yongsheng Zhu Chong Liu Chunlei Chen Xiaoting Lyu Zheng Chen Bin Wang Fuqiang Hu Hanxi Li Jiao Dai baigen cai Wei Wang School of Automation and Intelligence Beijing Jiaotong UniversityBeijing100044China Institute of Computing Technologies China Academy of Railway Sciences Corporation LimitedBeijing100081China School of Computer Science and Technology Beijing Jiaotong UniversityBeijing100044China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong UniversityBeijing100044China Institute of Infrastructure Inspection China Academy of Railway Sciences Corporation LimitedBeijing100081China Zhejiang Key Laboratory of Multi-Dimensional Perception Technology Application and CybersecurityHangzhou310053China

The development of Intelligent Railway Transportation Systems necessitates incorporating privacy-preserving mechanisms into AI models to protect sensitive information and enhance system *** learning offers a promising solution by allowing multiple clients to train models collaboratively without sharing private ***,despite its privacy benefits,federated learning systems are vulnerable to poisoning attacks,where adversaries alter local model parameters on compromised clients and send malicious updates to the server,potentially compromising the global model’s *** this study,we introduce PMM(Perturbation coefficient Multiplied by Maximum value),a new poisoning attack method that perturbs model updates layer by layer,demonstrating the threat of poisoning attacks faced by federated *** experiments across three distinct datasets have demonstrated PMM’s ability to significantly reduce the global model’s ***,we propose an effective defense method,namely CLBL(Cluster Layer By Layer).Experiment results on three datasets have confirmed CLBL’s effectiveness.

关键词： Privacy-preserving intelligent railway transportation system federated learning poisoning attacks defenses

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一种组合导航的自适应信息融合算法

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北京交通大学学报 2008年第2期32卷 88-93页

作者：刘江蔡伯根北京交通大学轨道交通控制与安全国家重点实验室北京100044

以GPS/INS组合导航系统为应用背景,针对组合导航系统信息融合的精度与稳定性要求,将简化的Sage-Husa自适应滤波算法与指数加权衰减记忆滤波算法相结合,提出了一种改进的自适应信息融合算法.仿真表明,改进的自适应算法解决了噪声统计特... 详细信息

以GPS/INS组合导航系统为应用背景,针对组合导航系统信息融合的精度与稳定性要求,将简化的Sage-Husa自适应滤波算法与指数加权衰减记忆滤波算法相结合,提出了一种改进的自适应信息融合算法.仿真表明,改进的自适应算法解决了噪声统计特性和模型参数不易确定的问题,能够有效的保证信息融合的精度和稳定性.在算法仿真的基础上,对在VC++6.0环境下算法进行了改进,给出了GPS/INS组合导航系统的结构及软件框架,通过实验验证了改进的自适应算法的实际应用价值.

关键词：组合导航信息融合自适应滤波全球定位系统惯性导航系统

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