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CPTED 在网络空间领域的多组分分析。

A Multi-Component Analysis of CPTED in the Cyberspace Domain.

机构信息

Center for Information Security Technology (CIST), Korea University, Seoul 02841, Korea.

Institue of Cyber Security & Privacy (ICSP), Korea University, Seoul 02841, Korea.

出版信息

Sensors (Basel). 2020 Jul 17;20(14):3968. doi: 10.3390/s20143968.

DOI:10.3390/s20143968
PMID:32708862
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7411980/
Abstract

The visual fidelity of a virtual environment lacks the exceedingly complex layers from the physical world, but the continuous improvements of image rendering technology and computation powers have led to greater demands for virtual simulations. Our study employs Crime Prevention through Environmental Design (CPTED) as a risk control measure and utilizes two principles: Access Control and Natural Surveillance. We conducted an experiment with (n-sample: 100) graduate students. For the experiment, we utilized the Factor Analysis of Information Risk (FAIR) to quantitatively analyze the risk. Furthermore, we adopted the lme4 package for R to estimate the mixed effect of the 6,242,880 observations retrieved from Kaggle. Based on the two experiments, we were able to critically evaluate the contributions of CPTED through a multi-component analysis. Our study investigates how spatial syntax and territorial demarcation may translate in the cyberspace realm. We found that the corollaries of the mophology in the virtual environment effects the distribution of crime. The results of our study discusses how to determine the criminogenic designs and capacity in the cyberspace realm.

摘要

虚拟环境的视觉逼真度缺乏物理世界中极其复杂的层次,但图像渲染技术和计算能力的不断提高,导致对虚拟模拟的需求越来越大。我们的研究将环境设计预防犯罪(CPTED)作为一种风险控制措施,并利用两个原则:访问控制和自然监控。我们对(n-样本:100)名研究生进行了实验。对于实验,我们利用信息风险的因素分析(FAIR)对风险进行定量分析。此外,我们还采用了 R 中的 lme4 包来估计从 Kaggle 检索到的 6,242,880 个观测值的混合效应。通过多组件分析,我们能够对 CPTED 的贡献进行批判性评估。我们的研究调查了空间句法和领土划分如何在网络空间领域中转化。我们发现,虚拟环境中形态的推论会影响犯罪的分布。我们的研究结果讨论了如何确定网络空间领域中的犯罪设计和能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/055a7ab722f0/sensors-20-03968-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/5fa762a0c248/sensors-20-03968-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/4c001812ad1f/sensors-20-03968-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/e8a615104bfc/sensors-20-03968-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/50d410618765/sensors-20-03968-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/525f58a9df51/sensors-20-03968-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/6e2c9226f33d/sensors-20-03968-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/3c9eb5987d0e/sensors-20-03968-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/055a7ab722f0/sensors-20-03968-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/5fa762a0c248/sensors-20-03968-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/4c001812ad1f/sensors-20-03968-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/e8a615104bfc/sensors-20-03968-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/50d410618765/sensors-20-03968-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/525f58a9df51/sensors-20-03968-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/6e2c9226f33d/sensors-20-03968-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/3c9eb5987d0e/sensors-20-03968-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7b/7411980/055a7ab722f0/sensors-20-03968-g008.jpg

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