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视觉传感器网络的广义威胁模型。

A Generalized Threat Model for Visual Sensor Networks.

机构信息

Georgia Institute of Technology, Atlanta, GA 30318, USA.

Joanneum Research, Klagenfurt 9020, Austria.

出版信息

Sensors (Basel). 2020 Jun 28;20(13):3629. doi: 10.3390/s20133629.

Abstract

Today, visual sensor networks (VSNs) are pervasively used in smart environments such as intelligent homes, industrial automation or surveillance. A major concern in the use of sensor networks in general is their reliability in the presence of security threats and cyberattacks. Compared to traditional networks, sensor networks typically face numerous additional vulnerabilities due to the dynamic and distributed network topology, the resource constrained nodes, the potentially large network scale and the lack of global network knowledge. These vulnerabilities allow attackers to launch more severe and complicated attacks. Since the state-of-the-art is lacking studies on vulnerabilities in VSNs, a thorough investigation of attacks that can be launched against VSNs is required. This paper presents a general threat model for the attack surfaces of visual sensor network applications and their components. The outlined threats are classified by the STRIDE taxonomy and their weaknesses are classified using CWE, a common taxonomy for security weaknesses.

摘要

如今,视觉传感器网络(VSN)广泛应用于智能家居、工业自动化或监控等智能环境中。在传感器网络的使用中,一个主要关注点是它们在存在安全威胁和网络攻击时的可靠性。与传统网络相比,传感器网络通常由于动态和分布式网络拓扑、资源受限的节点、潜在的大规模网络以及缺乏全局网络知识而面临更多的额外漏洞。这些漏洞使得攻击者可以发起更严重和复杂的攻击。由于现有技术缺乏对 VSN 漏洞的研究,因此需要对可以针对 VSN 发起的攻击进行彻底调查。本文提出了视觉传感器网络应用程序及其组件的攻击面的通用威胁模型。概述的威胁按 STRIDE 分类法进行分类,其弱点使用 CWE(安全弱点的通用分类法)进行分类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f63c/7374518/ea0aea970b59/sensors-20-03629-g001.jpg

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