提高移动人群感知数据可靠性的多维框架

IF 5 3区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Egyptian Informatics Journal Pub Date : 2024-08-09 DOI:10.1016/j.eij.2024.100518

Xu Wu , Yanjun Song , Junyu Lai

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引用次数: 0

摘要

移动人群感知（MCS）已成为一种前景广阔的新数据感知模式。在这种环境下，恶意攻击者很容易提交错误或不可信的数据。这极大地影响了 MCS 系统的正常运行和任务结果的真实性。因此，确保数据的可靠性正成为 MCS 的一个重要研究方向，尤其是在实时应用场景中。为此，我们提出了一个提高数据可靠性的多维框架，命名为 MDF。它整合了时间、空间环境和传感测量三个维度。通过一系列实验证明，MDF 优于现有方法。

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A multi-dimensional framework for improving data reliability in mobile crowd sensing

Mobile Crowd Sensing (MCS) has become a promising new data perception paradigm. It is to be able to easily submit the wrong or untrusted data for the malicious attackers in such an environment. This greatly affects the normal operation of the MCS system and the authenticity of task results. Therefore, ensuring the reliability of data is becoming a key research direction in MCS, especially for real-time application scenarios. For this purpose, we propose a multi-dimensional framework for improving data reliability, named MDF. It integrates three dimensions of temporal, spatial context and sensing measurement. Through a series of experiments, it is demonstrated that MDF outperforms existing methods.

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来源期刊

Egyptian Informatics Journal Decision Sciences-Management Science and Operations Research

CiteScore

11.10

自引率

1.90%

发文量

审稿时长

110 days

期刊介绍： The Egyptian Informatics Journal is published by the Faculty of Computers and Artificial Intelligence, Cairo University. This Journal provides a forum for the state-of-the-art research and development in the fields of computing, including computer sciences, information technologies, information systems, operations research and decision support. Innovative and not-previously-published work in subjects covered by the Journal is encouraged to be submitted, whether from academic, research or commercial sources.