Applications for Wireless Visual Sensor Networks

2011 ◽  
pp. 325-339 ◽  
Author(s):  
Johannes Karlsson ◽  
Tim Wark ◽  
Keni Ren ◽  
Karin Fahlquist ◽  
Haibo Li
Keyword(s):  
Interaction Design ◽  
Large Scale ◽  
Research Work ◽  
The Arctic ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Visual Sensor Networks ◽  
Work Related ◽  
New Type ◽  
Set Up

In this chapter we will describe our work to set up a large scale wireless visual sensor network in a Swedish zoo. It is located close to the Arctic Circle making the environment very hard for this type of deployment. The goal is to make the zoo digitally enhanced, leading to a more attractive and interactive zoo. To reach this goal the sensed data will be processed and semantic information will be used to support interaction design, which is a key component to provide a new type of experience for the visitors. In this chapter we will describe our research work related to the various aspects of a digital zoo.

Security Framework for Smart Visual Sensor Networks

2019 ◽  
pp. 230-252
Author(s):  
G. Suseela ◽  
Y. Asnath Victy Phamila
Keyword(s):  
Sensor Networks ◽  
Embedded System ◽  
Image Encryption ◽  
Image Sensor ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Partial Encryption ◽  
Visual Sensor Networks ◽  
Resource Limited ◽  
Scalar Data

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

Visual Sensor Network Processing and Preventative Steganalysis

2011 ◽  
pp. 340-357
Author(s):  
Julien Sebastien Jainsky ◽  
Deepa Kundur
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
High Rate ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Visual Sensor Networks ◽  
Steganographic Attacks ◽  
Wireless Visual Sensor Networks ◽  
The Moment ◽  
Rate Of Success

In this chapter, we discuss the topic of security in wireless visual sensor networks. In particular, attention is brought to steganographic security and how it can be discouraged without challenging the primary objectives of the network. We motivate the development and implementation of more lightweight steganalytic solutions that take into account the resources made available by the network’s deployment and its application in order to minimize the steganalysis impact on the WVSN workload. The concept of preventative steganalysis is also introduced in this chapter as a means to protect the network from the moment it is deployed. Preventative steganalysis aims at discouraging any potential steganographic attacks by processing the WVSN collected data such that the possibility of steganography becomes very small and the steganalysis leads to high rate of success.

scholarly journals A Generalized Threat Model for Visual Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3629
Author(s):  
Jennifer Simonjan ◽  
Sebastian Taurer ◽  
Bernhard Dieber
Keyword(s):  
Sensor Networks ◽  
Global Network ◽  
Large Network ◽  
Distributed Network ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Visual Sensor Networks ◽  
Threat Model ◽  
Network Applications ◽  
Attack Surfaces

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.

TOPICAL ISSUES OF STUDYING SOCIAL PROBLEMS OF THE RUSSIAN ARCTIC

2020 ◽  
pp. 18-26
Author(s):  
Julija V. Аndreeva ◽  
Keyword(s):  
Large Scale ◽  
Research Work ◽  
Arctic Region ◽  
Well Being ◽  
The Arctic ◽  
The Social ◽  
Northern Regions ◽  
Russian North ◽  
Scientific Potential ◽  
Intellectual Potential

The article analyses the most relevant aspects of Arctic research, which are gaining momentum in recent years. The most dynamic thematic ar- eas include the humanitarian issues of the development of the Russian North. The research focuses on the assessment of the peculiarities of the formation and reproduction of human capital in the Arctic zone of the Russian Federation the development of the creative and intellectual potential of Russian polar cities. The author notes that research into the social well-being of the population of the Rus- sian Northern regions has become an important direction of research work carried out over the past decades. In studies of the social well-being of the inhabitant of the Arctic region, the authors problematize the key “zones of disadvantage” in the system of assessing the population, and, first of all, the issues of protection from those social dangers that the population find for itself. Summarizing the state of the Arctic research, the author proposes to move away from overly localized coverage of Arctic problems. Large-scale sociological works, which, in our opin- ion, have a certain substantial scientific potential, provided that they are fully implemented, it seems, are now at the stage of their theoretical conceptualization and methodological search.

Security Framework for Smart Visual Sensor Networks

2021 ◽  
pp. 406-423
Author(s):  
G. Suseela ◽  
Y. Asnath Victy Phamila
Keyword(s):  
Sensor Networks ◽  
Embedded System ◽  
Image Encryption ◽  
Image Sensor ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Partial Encryption ◽  
Visual Sensor Networks ◽  
Resource Limited ◽  
Scalar Data

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

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