Geographic-Region Monitoring by Drones in Adversarial Environments

IF 1.2 Q4 REMOTE SENSING

ACM Transactions on Spatial Algorithms and Systems Pub Date : 2021-11-02 DOI:10.1145/3611009

O. Wolfson, Prabin Giri, S. Jajodia, Goce Trajcevski

引用次数: 2

Abstract

We consider surveillance of a geographic region by a collaborative system of drones. The drones assist each other in identifying and managing activities of interest on the ground. We also consider an adversary who can create both genuine and fake activities on the ground. The objective of the adversary is to use fake activities to maximize the response time to genuine activities. We present two collaboration algorithms and analyze their response times, as well as the adversary’s efforts in terms of the number of fake activities required to achieve a certain response time.

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无人机在对抗环境中的地理区域监测

我们考虑通过无人机协作系统监视一个地理区域。无人机相互协助识别和管理地面上感兴趣的活动。我们还考虑到一个既能在地面上制造真实活动又能在地面上制造虚假活动的对手。攻击者的目标是使用虚假活动来最大化对真实活动的响应时间。我们提出了两种协作算法，并分析了它们的响应时间，以及对手在达到一定响应时间所需的虚假活动数量方面的努力。

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

ACM Transactions on Spatial Algorithms and Systems REMOTE SENSING-

CiteScore

4.40

自引率

5.30%

发文量

期刊介绍： ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.