While interest in using 3D scanning technology for crime scene investigation (CSI) has grown in recent years, a number of barriers still remain that prevent its wide adoption in the criminal justice system. One such barrier comes from the lack of tools that can validate a 3D scan and verify that it has not been manipulated. While a great deal of research has gone into the detection of manipulations for 2D images, the detection of manipulations for 3D scenes has yet to be fully realized.

This paper introduces a series of techniques to detect if a 3D point cloud generated from a LiDAR scan has been subsequently manipulated. These techniques exploit fundamental structures inherent in the collection and storage of these types of data. While the proposed techniques are able to detect a number of different types of manipulations, their limitations are also discussed. The goal of this work is to provide a foundation for the creation of a validation toolkit that can ensure 3D scan data is valid and unaltered.

尽管近年来对使用3D扫描技术进行犯罪现场调查（CSI）的兴趣有所增长，但仍然存在许多障碍，阻碍了其在刑事司法系统中的广泛采用。此类障碍之一是由于缺少可以验证3D扫描并确认未进行操作的工具。尽管对2D图像的操作检测已进行了大量研究，但对3D场景的操作的检测尚未完全实现。

本文介绍了一系列技术，以检测随后是否处理过由LiDAR扫描生成的3D点云。这些技术利用了这些类型的数据的收集和存储中固有的基本结构。虽然所提出的技术能够检测多种不同类型的操作，但它们的局限性也得到了讨论。这项工作的目的是为创建验证工具箱提供基础，该验证工具箱可以确保3D扫描数据有效且不变。