Security Framework for Smart Visual Sensor Networks

Security Framework for Smart Visual Sensor Networks

G. Suseela (VIT University, India) and Y. Asnath Victy Phamila (VIT University, India)
DOI: 10.4018/978-1-5225-8241-0.ch012
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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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The contemporary advancements in CMOS technology, multimedia systems together with communication technologies empowered image communication over resource constrained Visual Sensor Network (VSN). The image communication is more significant than scalar data communication, hence it has attained wide applications like critical infrastructure monitoring, habitat monitoring, surveillance, traffic monitoring, industrial control systems, smart home systems and many more. Recently (Paek, Hicks, Coe, & Govindan, 2014) has reported the bird nest monitoring system at the James San Jacinto Mountain Reserve and the system assisted the biologists to study the life of birds during the nesting spell to unbox the biological interrogations connected to the laying, incubation and hatching of eggs and way of life of the new born nestlings in the nests. Yet quite a lot of new commercial applications which require visual support are emerging out embedded VSN.

Figure 1.

VSN architecture and senor mote architecture


In Visual Sensor Network the VS nodes are deployed in places where they can be used to monitor and sense environmental conditions by collaborating and communicating with each other over the wireless communication channels. Smart cameras which are capable of processing the sensed images onboard can be connected to Visual Sensor Networks. Typically, Visual Sensor Networks are built with resource-limited devices. These networks are resource restricted systems with limited memory, processing speed, computational power and bandwidth. Visual Sensor Networks are autonomous systems capable of capturing, processing and communicating the image in difficult-to-access regions without exclusive network infrastructure in adhoc fashion. The typical VSN architecture and Senor Mote architecture are shown in Figure 1 (Suseela & Phamila, 2016). Generally, wireless networks prefer energy efficient computation and communication for better lifetime of the network. As images contain more redundancies, processing and communicating the image data will consume more energy. Hence for the increased active lifetime of the network image processing algorithms exclusively developed for energy efficiency and low resource utilization must be adopted in VSN. The inherent nature of visual data in the form of images is self-descriptive. Therefore, the secrecy and privacy protection are more essential in wireless communication networks, as wireless links are more prone to security threats by nature (Gonalves & Costa, 2015).


Visual Sensor Network Security Requirement

In these modern days, VSNs are gaining more attention by both private and public communities and security becomes a prominent issue to address. The visual data are more sensitive than scalar data when an image data is meddled the information content of the transmitted image will be revealed abruptly; while tampering the scalar numeric data will not unveil the meaning of it is and symbolize just as a number. The visual data are easily understood by a human, they will not conceal the privacy features of the image and reveal the genteel clues about time, location information etc. The VSN is predisposed and can be dismayed to compromise the network task or to acquire unauthorized admission to pertinent information. The key security requirements for Visual Sensor Networks are data integrity, confidentiality, authenticity, freshness, localization, controlled access and privacy preservation (Suseela & Phamila, 2016), (Costa, Figuerêdo & Oliveira, 2017).

Key Terms in this Chapter

Image Cryptography: The image cryptography is one of the practice employed for securing the information content of the image using strong encryption algorithms.

Secured Transmission: Secure transmission refers to transfer of data from source to destination over the communication channel meeting out the basic security requirements like confidentiality, data integrity, authenticity, etc., ensuring that the information coded in the transmitted data is not seeped in the transit.

Chaotic Systems: Chaotic systems are time dynamic system whose state will vary with time. Based on time there are two types of chaotic systems namely, discrete chaotic systems and continuous chaotic systems.

Image compression: The process of removing the redundancies present among the pixels of the image and reducing the size of image in compact form for efficient storage and transmission.

Image Transform: Image transform is a two-dimensional signal processing technique which decorrelates the data very well allows an image analyzer to work directly on the significant and insignificant components of the data.

Selective Encryption: The process of encrypting only the most significant and sensitive portion of the data is known as selective or partial encryption.

Entropy: Entropy is a measure of amount of uncertainty or disorder present in the system within the possible probability distribution. The entropy and amount of unpredictability are directly proportional to each other.

Differential Attack: The intruders try to break the encryption system by injecting minimum changes into an image. They attempt to study the statistical correlation that exists between the encrypted images of original and modified image.

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