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MuLViS: Multi-Level Encryption Based Security System for Surveillance Videos

Qiao, Y; Ansari, MS; Lee, B; Shifa, A; Asghar, MN; Fleury, M; Kanwal, N; Herbst, M

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Authors

Y Qiao

MS Ansari

B Lee

A Shifa

MN Asghar

M Fleury

M Herbst



Abstract

Video Surveillance (VS) systems are commonly deployed for real-time abnormal event detection and autonomous video analytics. Video captured by surveillance cameras in real-time often contains identifiable personal information, which must be privacy protected, sometimes along with the locations of the surveillance and other sensitive information. Within the Surveillance System, these videos are processed and stored on a variety of devices. The processing and storage heterogeneity of those devices, together with their network requirements, make real-time surveillance systems complex and challenging. This paper proposes a surveillance system, named as Multi-Level Video Security (MuLViS) for privacy-protected cameras. Firstly, a Smart Surveillance Security Ontology (SSSO) is integrated within the MuLViS, with the aim of autonomously selecting the privacy level matching the operating device's hardware specifications and network capabilities. Overall, along with its device-specific security, the system leads to relatively fast indexing and retrieval of surveillance video. Secondly, information within the videos are protected at the times of capturing, streaming, and storage by means of differing encryption levels. An extensive evaluation of the system, through visual inspection and statistical analysis of experimental video results, such as by the Encryption Space Ratio (ESR), has demonstrated the aptness of the security level assignments. The system is suitable for surveillance footage protection, which can be made General Data Protection Regulation (GDPR) compliant, ensuring that lawful data access respects individuals' privacy rights.

Acceptance Date Sep 18, 2020
Publication Date Oct 8, 2020
Journal IEEE ACCESS
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 177131 - 177155
DOI https://doi.org/10.1109/ACCESS.2020.3024926
Publisher URL https://ieeexplore.ieee.org/document/9199837

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