Resisting TUL attack: balancing data privacy and utility on trajectory via collaborative adversarial learning

IF 2.2 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Geoinformatica Pub Date : 2023-10-21 DOI:10.1007/s10707-023-00507-3

Yandi Lun, Hao Miao, Jiaxing Shen, Renzhi Wang, Xiang Wang, Senzhang Wang

引用次数: 0

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抵抗TUL攻击:通过协作对抗学习在轨迹上平衡数据隐私和效用

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geoinformatica 地学-计算机：信息系统

CiteScore

5.60

自引率

10.00%

发文量

审稿时长

6 months

期刊介绍： GeoInformatica is located at the confluence of two rapidly advancing domains: Computer Science and Geographic Information Science; nowadays, Earth studies use more and more sophisticated computing theory and tools, and computer processing of Earth observations through Geographic Information Systems (GIS) attracts a great deal of attention from governmental, industrial and research worlds. This journal aims to promote the most innovative results coming from the research in the field of computer science applied to geographic information systems. Thus, GeoInformatica provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of the use of computer science for spatial studies.