文献类型：期刊文献

中文题名：利用扩展卡尔曼动态编码的智慧航道系统船舶定位安全保护

英文题名：Security Protection for Vessel Positioning in Smart Waterway Systems Based on Extended Kalman Filter-Based Dynamic Encoding

作者：唐风建[1];闫霞[1];孙泽仪[2];朱钊伟[3];杨文[2]

机构：[1]长江上海航道处,上海200011;[2]华东理工大学信息科学与工程学院,上海200237;[3]江苏国信靖江发电有限公司,泰州214500

年份：2026

卷号：48

期号：4

起止页码：1539

中文期刊名：电子与信息学报

外文期刊名：Journal of Electronics & Information Technology

收录：;EI(收录号：20263221263156);北大核心:【北大核心2023】；

基金：国家重点研发计划(2023YFF1204805);国家自然科学基金重点项目(62336005)。

语种：中文

中文关键词：隐私保护;船舶定位;扩展卡尔曼滤波;动态编码;分布式估计

外文关键词：Vessel positioning;Privacy protection;Extended Kalman Filter(EKF);Dynamic encoding;Distributed estimation

摘要：随着智能航运系统的快速发展,船舶定位数据在无线传输过程中面临严重的隐私泄露风险。传统隐私保护方法如差分隐私和同态加密存在数据失真、计算开销大或依赖高成本通信链路等问题,难以在保证数据完整性的同时实现高效防护。本文针对船舶稳定系统的特点,提出一种基于时间扰动增强的动态编码方案。该方案结合扩展卡尔曼滤波(EKF),在编码过程中引入不稳定的时间扰动项,利用接收方对发送方发出的信息进行确认这一机制(ACK反馈)实现参考时间同步,并利用共享随机种子独立生成同步的扰动项。理论分析与仿真实验表明,该方案能够在合法接收方实现近乎零精度损失的状态估计的同时,使窃听者在单次丢包后解码误差随时间呈指数增长趋势,有效阻断单通道与多通道窃听攻击。方案采用共享随机种子同步机制,避免了复杂的密钥管理,显著降低了通信与计算开销,适用于资源受限的海上无线传感器网络环境,为船舶安全定位提供了有效保障。
Objective With the rapid development of intelligent shipping systems,vessel positioning data face severe privacy leakage risks during wireless transmission.Traditional privacy-preserving methods,such as differential privacy and homomorphic encryption,suffer from data distortion,high computational overhead,or reliance on costly communication links,making it difficult to achieve both data integrity and efficient protection.This study addresses the characteristics of vessel stabilization systems and proposes a dynamic encoding scheme enhanced by time-varying perturbations.By integrating the Extended Kalman Filter(EKF)and introducing unstable temporal perturbations during encoding,the scheme uses receiver-side acknowledgments(ACK feedback)to achieve reference-time synchronization and independently generates synchronized perturbations through a shared random seed.Theoretical analysis and simulations show that the proposed method achieves nearly zero precision loss in state estimation for legitimate receivers,whereas decoding errors of eavesdroppers grow exponentially after a single packet loss,effectively countering both single-and multi-channel eavesdropping attacks.The shared-seed synchronization mechanism avoids complex key management and reduces communication and computational costs,making the scheme suitable for resource-constrained maritime wireless sensor networks.Methods The proposed dynamic encoding scheme introduces a time-varying perturbation term into the encoding process.The perturbation is governed by an unstable matrix to induce exponential error growth for eavesdroppers.The encoded signal is constructed from the difference between the current state estimate and a time-scaled reference state,combined with the perturbation term.A shared random seed between legitimate parties enables deterministic and synchronized generation of the perturbation sequence without online key exchange.At the legitimate receiver,the perturbation is canceled during decoding,enabling accurate state recovery.Local state estimation at each sensor node is performed using EKF,and the overall communication process is reinforced by acknowledgment-based synchronization to maintain consistency between the sender and receiver.Results and Discussions Simulations are conducted in a wireless sensor network with four sensors tracking vessel states,including position,velocity,and heading.The results indicate that legitimate receivers achieve nearly zero estimation error(Fig.3),Simulations were conducted in a wireless sensor network with multisensors tracking vessel states such as position,velocity,and heading.The results show that legitimate receivers achieve nearly zero estimation error(Fig.3),while eavesdroppers experience exponentially growing errors after a single packet loss.The error growth rate correlates with the instability of the perturbation matrix,confirming the theoretical divergence.In multi-channel scenarios,independent perturbation sequences per channel prevent cross-channel correlation attacks.The scheme maintains low communication and computational overhead,making it practical for maritime environments.Furthermore,the method demonstrates strong adaptability to packet loss and channel variations,fulfilling SOLAS requirements for data integrity and reliability.Conclusions A dynamic encoding scheme with time-varying perturbations is proposed for privacy-preserving vessel state estimation.By integrating EKF with an unstable perturbation mechanism,the method ensures high estimation precision for legitimate users and exponential error growth for eavesdroppers.The main contributions are as follows:(1)an encoding framework that achieves zero precision loss for legitimate receivers;(2)a lightweight synchronization mechanism based on shared random seeds,which removes complex key management;and(3)theoretical guarantees of exponential error divergence for eavesdroppers under single-or multi-channel attacks.The scheme is robust to packet loss and channel asynchrony,complies with SOLAS data integrity requirements,and is suitable for resource-limited maritime networks.Future work will extend the method to nonlinear vessel dynamics,adaptive perturbation optimization,and validation in real maritime communication environments.