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

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

doi:10.1155/2019/1625678

Rafik Hamza, Alzubair Hassan + Show 3 more

Open Access

https://doi.org/10.1155/2019/1625678

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Journal: Complexity	Publication Date: Dec 9, 2019
Citations: 27	License type: CC BY 4.0

Affiliation: Guangzhou University

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.

Highlights

Digital technology IoT-based becomes an integral part of strategy formulations in human life [1]
Security Analysis. e fractional order in discrete fractional random transform (DFRT) and the initial parameters of the Chen chaotic system are selected as secret keys. e chaotic maps are known by the sensibility of its initial values and controlling parameters
We can estimate the keyspace based on this sensibility evaluation of the selected secret keys (α, x0, y0, z0, a, b, and c). e keys should be sensitive enough to change the encrypted data. is means that any adjustment of the secret keys should change completely the encrypted data. us, we can estimate that the keyspace for a chaotic sequence is around 1090 ≃ 2300. is is the minimum space key that can be considered in our proposed framework

Summary

Introduction

Digital technology IoT-based becomes an integral part of strategy formulations in human life [1]. Is paper proposes a cryptosystem framework based on the summarization technique using compression and encryption schemes. The proposed framework encrypts the compressed data using a lightweight image encryption scheme In this part, Chen’s chaotic map is employed to generate two random keys: one key is to confuse the image pixels (a permutation process) and the second key is a random matrix employed in a discrete fractional random transform. (i) is paper proposes a cryptosystem framework based on a cluster summarization technique with compression and encryption algorithms (ii) e proposed cryptosystem requires low computational power and decreased bandwidth and storage terms (iii) e proposed cryptosystem uses randomized keys (instead of a static block cipher) based on Chen’s chaotic map (iv) e proposed cryptosystem can encrypt multiple frames once instead of one-to-one traditional encryption is paper is organized as follows.

The Proposed Framework for Surveillance Systems

Evaluation

Conclusion and Future Work