Local Trajectory Privacy Protection in 5G Enabled Industrial Intelligent Logistics

Abstract

The value of trajectory data lies mainly in the spatiotemporal correlation. However, the existing privacy protection methods ignore the spatio-temporal correlation of trajectory data, resulting in a large error in trajectory proportion estimation and Top-K classification. For the privacy of truck trajectory in intelligent logistics, the location and trajectory data perturbation method based on quadtree indexing is proposed, which leverages location generalization and local differential privacy techniques. Our proposed algorithms are suitable for datasets with a large sample space and can protect the trajectory privacy of truck drivers while preserving the strong correlation between adjacent spatio-temporal nodes in the trajectory. The results of simulation on a real trajectory dataset show that the proposed methods not only meet the trajectory privacy requirements of users but also have a good performance in trajectory proportion estimation and Top-K classification.Index Terms-Intelligent logistics; trajectory privacy; spatiotemporal correlation; local differential privacy; quadtree indexing I. INTRODUCTION I NTELLIGENT logistics is an important application of the Industrial Internet of Things (IIoT) and a key part of the whole IIoT system. The development of intelligent logistics is inseparable from the support of communication techniques. The data transmission among the logistics nodes such as trucks, warehouses, workers, and target customers requires high quality communication services, the supporting technology for the evolution of intelligent logistics, such as Internet of Things, cloud computing, big data analytics, artificial intelligence [1], etc., and relies on the communication infrastructure with large capacity, high broadband, low delay, and high reliability. At present, the 5G wireless communications with the characteristics of ultra-high bandwidth, wide

Comparison of Features in Content Coverage and Presentation of Complex Numbers in Textbooks of China, Japan and Singapore

“…Numerous experimental results have demonstrated that our proposed scheme significantly outperforms the baseline schemes and can effectively reduce system latency. There still exist some challenges to be addressed, such as security and privacy issues of avatar data migration [45], and energy-efficient decisions for migration [46]. In our future work, we consider using blockchain or other advanced privacy-preserving artificial intelligence algorithms to achieve data security and privacy protection during avatar migration in vehicular metaverses.…”

5G in Logistics 4.0: potential applications and challenges

“…The articles dealing with transportation are all related to the traceability of both parcels and vehicles, in particular concerning various critical issues concerning mainly cyber security [29,30] and the need to integrate different technologies, databases and formats [31,32] even among different countries [33].…”

“…Embedded Microprocessors and Edge Computing are cited as promising technologies to perform efficient datapreprocessing combined to 5G: the first through the filtering of relevant information for the specific application and the latter through a decentralized computational model in which data, particularly critical from the most latencysensitive applications, are analyzed directly where they are detected [33,37]. Logistics companies use cloud systems as a platform for storing information [29] and, as highlighted by [5,18,26], Blockchain constitutes one of the most advanced and reliable technology to ensure the data security in distributed, open environments, in accordance to the requirements of 5G networks architectures. Finally, technologies for data analytics such as Machine Learning, Artificial Intelligence, Simulation, and Augmented Reality have been cited in research studies that exploit the 5G network to feed intelligent optimisation systems, able to leverage real-time data from equipment (e.g., drones and AGVs) to provide a timely decision about transportation routes, last-mile delivery, supply chain networks, malfunctioning recovery [21,26,34,36,37,41].…”

A differential privacy trajectory data storage and publishing scheme based on radix tree

“…And a privacy‐level assignment method based on stay points and frequent sub‐trajectories is proposed, which uses differential privacy technology to perturb the location points on the user's trajectory before releasing the trajectory data. Yang et al 17 proposed a location trajectory data perturbation method based on quadtree index. This method uses location generalization and local differential privacy technology, which can not only protect trajectory privacy but also maintain the strong correlation between adjacent spatiotemporal nodes in the trajectory.…”