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Open AccessArticle

A Generalized Threat Model for Visual Sensor Networks

by Jennifer Simonjan 1,†, Sebastian Taurer 2,† and Bernhard Dieber 2,*,†
1
Georgia Institute of Technology, Atlanta, GA 30318, USA
2
Joanneum Research, 9020 Klagenfurt, Austria
*
Author to whom correspondence should be addressed.
All authors contributed equally to threat modeling. Jennifer Simonjan and Bernhard Dieber additionally contributed equally to writing the paper.
Sensors 2020, 20(13), 3629; https://doi.org/10.3390/s20133629
Received: 15 May 2020 / Revised: 16 June 2020 / Accepted: 23 June 2020 / Published: 28 June 2020
(This article belongs to the Special Issue Machine Learning for IoT Applications and Digital Twins)
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. View Full-Text
Keywords: visual sensor networks; security; threat model; distributed systems visual sensor networks; security; threat model; distributed systems
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Simonjan, J.; Taurer, S.; Dieber, B. A Generalized Threat Model for Visual Sensor Networks. Sensors 2020, 20, 3629.

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