An Efficient Cryptosystem for Video Surveillance in the Internet of Things Environment

Rafik Hamza, Alzubair Hassan, Teng Huang, Lishan Ke and Hongyang Yan

Complexity, 2019, vol. 2019, 1-11

Abstract:

Surveillance systems paradigm envisions the pervasive interconnection and cooperation of interactive devices over the Internet infrastructure. Nevertheless, dissemination and processing of surveillance video amid the Internet of Things (IoT) applications become a susceptible issue due to the large volume and the significant information of these data. Moreover, surveillance devices on IoT have very limited resources such as memory and storage. The actual security methods are not quite appropriate for surveillance IoT systems. Thus, a particular cryptosystem technique is required for surveillance data security. In this paper, we propose an efficient cryptosystem to secure IoT-based surveillance systems. The proposed cryptosystem framework contains three parts. First, a lightweight automatic summarization technique based on a fast histogram-clustering approach is used to extract the keyframes from the surveillance video. Then, we employ a discrete cosine transform (DCT) technique to compress the extracted data size. Finally, the proposed framework performs an efficient image encryption algorithm by employing a discrete fractional random transform (DFRT). The testing results and analysis confirm the features of the proposed cryptosystem on surveillance systems. The proposed framework is fast and ensures secure and efficient real-time processing by minimizing the transmission cost and storage.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:1625678

DOI: 10.1155/2019/1625678

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