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Cited by 43Video Surveillance and Tracking MethodsChaos-based Image/Signal EncryptionCryptography and Data Security

MuLViS: Multi-level encryption based security system for surveillance videos

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Shifa, Amna, Asghar, Mamoona N., Fleury, Martin, Kanwal, Nadia, Ansari, Mohammad S., Lee, Brian, Herbst, Marco, Qiao, Yuansong·2020·IEEE Access
DOI 10.1109/access.2020.3024926
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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.

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Cited by

Sorted by citations

Authors
Shifa, A., Asghar, M. N., Fleury, M., Kanwal, N., Ansari, M. S., Lee, B., Herbst, M., & Qiao, Y.
Affiliations
  • Islamia University of Bahawalpur (PK)
  • Athlone Institute of Technology (IE)
  • University of Suffolk (GB)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020
Volume
8
Pages
177131-177155
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2020.3024926
OpenAlex
W3092327016
Cited by
43
References
3
Citations by year
2026: 1 · 2025: 11 · 2024: 11 · 2023: 8 · 2022: 7 · 2021: 5
FWCI
1.94
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Access (publishedVersion, cc-by)
  • Keele Research Repository (Keele University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Research@THEA (submittedVersion, cc-by)
Funders
  • Marie Sklodowska-Curie (MSC) Career-FIT Postdoctoral Fellowship (MF 2018-0179)
  • European Union’s Horizon2020 Research and Innovation Programme through the MSC (713654)
  • Science Foundation Ireland (SFI 16/RC/3918)
  • European Regional Development Fund
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
  • Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
Keywords
video surveillance, multi-level encryption, video indexing and retrieval, video streaming security, GDPR compliance, personal data protection

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