Cited by 69Digitalization, Law, and RegulationPrivacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Visual Surveillance Within the EU General Data Protection Regulation: A Technology Perspective

Open access
Asghar, Mamoona N., Kanwal, Nadia, Lee, Brian, Fleury, Martin, Herbst, Marco, Qiao, Yuansong·2019·IEEE Access

Abstract

From an individual's perspective, technological advancement has merits and demerits. Video captured by surveillance cameras while a person goes about their daily life may improve their personal safety but the images collected may also represent an invasion of their privacy. Because of the ease of digital information sharing, there exists a need to protect that visual information from illegal utilization by untrusted parties. The European parliament has ratified the General Data Protection Regulation (GDPR), which has been effective since May 2018 with a view to ensuring the privacy of European Union (EU) citizens' and visitors' personal data. The regulation has introduced data safeguards through Pseudonymisation, Encryption, and Data protection-by-design. However, the regulation does not assist with technical and implementation procedures, such as video redaction, to establish those safeguards. This paper refers to the GDPR term “personal data” as “visual personal data” and aims to discuss regulatory safeguards of visual privacy, such as reversible protection, from the technological point-of-view. In the context of GDPR, the roles of machine learning (i.e. within computer vision), image processing, cryptography, and blockchain are explored as a way of deploying Data Protection-by-Design solutions for visual surveillance data. The paper surveys the existing market-based data protection solutions and provides suggestions for the development of GDPR-compliant Data Protection-by-Design video surveillance systems. The paper is also relevant for those entities interacting with EU citizens from outside the EU and for those regions not currently covered by such regulation that may soon implement similar provisions.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/access.2019.2934226

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Academic circles have different definitions of personal information, and different countries espouse different ideological expressions according to their own laws and regulations.

    “At present, academic circles have different definitions of personal information, and different countries espouse different ideological expressions according to their own laws and regulations [109].”

    From A Survey of IoT Privacy Security: Architecture, Technology, Challenges, and Trends (2024) · cites this paper as [109]

    The Introduction and “GDPR Description and Definitions” section discuss how GDPR defines personal data; Section II describes harmonizing data-protection law across EU countries. Our copy does not say that academic definitions differ or that countries express differing concepts of personal information under their own laws (searched for academic definitions and country-specific legal definitions). The retrieved passages have no page numbers. (LLM, conf=0.75)

    Experimental — accuracy not yet measured
  • Data has become an important resource for the development of the information society and the cornerstone of the development of the IoT industry.

    “Data has become an important resource for the development of the information society and the cornerstone of the development of the IoT industry [109].”

    From A Survey of IoT Privacy Security: Architecture, Technology, Challenges, and Trends (2024) · cites this paper as [109]

    The Introduction discusses digitized collection of personal data and its use by companies, but does not describe data as a resource for developing the information society. Searches for the claimed role of data in IoT industry development found no passage addressing it; the paper instead focuses on GDPR-compliant visual surveillance. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 37

  1. A. Cavallaro, ''Privacy in video surveillance,'' IEEE Signal Process. Mag., vol. 24, no. 2, pp. 166-168, Mar. 2007.
  2. Q. M. Rajpoot and C. D. Jensen, ''Video surveillance: Privacy issues and legal compliance,'' in Promoting Social Change and Democracy Through Information Technology, V. Kumar and J. Svenson, Eds. Hershey, PA, USA: IGI Global, 2015, ch. 4, pp. 69-92.
  3. D. George, K. Reutimann, and A. Tamò-Larrieux, ''GDPR bypass by design? Transient processing of data under the GDPR,'' SSRN Electron. J., Aug. 2018.
  4. S. Stalla-Bourdillon and A. Knight, ''Anonymous data v. personal data- false debate: An EU perspective on anonymization, pseudonymization and personal data,'' Wisconsin Int. Law J., vol. 34, no. 2, pp. 284-322, 2017.
  5. S. Gilad-Gutnick, E. S. Harmatz, K. Tsourides, G. Yovel, and P. Sinha, ''Recognizing facial slivers,'' J. Cogn. Neurosci., vol. 30, no. 7, pp. 951-962, Jul. 2018.
  6. I. Bouchrika and M. S. Nixon, ''People detection and recognition using gait for automated visual surveillance,'' in Proc. IET Conf. Crime Secur., 2006, pp. 576-581.
  7. V. B. Semwal, N. Gaud, and G. C. Nandi, ''Human gait state prediction using cellular automata and classification using ELM,'' in Proc. Mach. Intell. Signal Anal., 2019, pp. 135-145.
  8. L. van Zoonen, ''Privacy concerns in smart cities,'' Government Inf. Quart., vol. 33, no. 3, pp. 472-480, 2016.
  9. R. Buyya, S. T. Selvi, and X. Chu, Object Oriented Programming With Java: Essentials and Applications. New York, NY, USA: McGraw-Hill, 2009.
  10. A. Romanou, ''The necessity of the implementation of Privacy by Design in sectors where data protection concerns arise,'' Comput. Law Secur. Rev., vol. 34, no. 1, pp. 99-110, 2018.
  11. S. Sah, A. Shringi, R. Ptucha, A. M. Burry, and R. P. Loce, ''Video redaction: A survey and comparison of enabling technologies,'' J. Electron. Imag., vol. 26, no. 5, 2017, Art. no. 051406.
  12. P. Sinha, B. Balas, Y. Ostrovsky, and R. Russell, ''Face recognition by humans: Nineteen results all computer vision researchers should know about,'' Proc. IEEE, vol. 94, no. 11, pp. 1948-1962, Nov. 2006.
  13. Z. Li and F. Zhou, ''FSSD: Feature fusion single shot multibox detec- tor,'' Dec. 2017, arXiv:1712.00960. [Online]. Available: https://arxiv.org/ abs/1712.00960 · arXiv
  14. J. R. Padilla-López, A. A. Chaaraoui, and F. Flórez-Revuelta, ''Visual privacy protection methods: A survey,'' Expert Syst. Appl., vol. 42, no. 9, pp. 4177-4195, 2015.
  15. M. Mourby, E. Mackey, M. Elliot, H. Gowans, S. E. Wallace, J. Bell, H. Smith, S. Aidinlis, and J. Kaye, ''Are 'pseudonymised' data always personal data? Implications of the GDPR for administrative data research in the UK,'' Comput. Law Secur. Rev., vol. 34, no. 2, pp. 222-233, 2018.
  16. J. Flusser, S. Farokhi, C. Höschl, T. Suk, B. Zitová, and M. Pedone, ''Recognition of images degraded by Gaussian blur,'' IEEE Trans. Image Process., vol. 25, no. 2, pp. 790-806, Feb. 2016.
  17. T. Gerstner, D. DeCarlo, M. Alexa, A. Finkelstein, Y. Gingold, and A. Nealen, ''Pixelated image abstraction with integrated user constraints,'' Comput. Graph., vol. 37, no. 5, pp. 333-347, 2013.
  18. Y. Kusama, H. Kang, and K. Iwamura, ''Mosaic-based privacy-protection with reversible watermarking,'' in Proc. 12th Int. Joint Conf. e-Bus. Telecommun., Jul. 2015, pp. 98-103.
  19. A. Erdélyi, T. Barát, P. Valet, T. Winkler, and B. Rinner, ''Adap- tive cartooning for privacy protection in camera networks,'' in Proc. 11th IEEE Int. Conf. Adv. Video Signal Based Surveill., Aug. 2014, pp. 44-49.
  20. J. Gomes and L. Velho, ''Warping and Morphing,'' in Proc. Image Process. Comput. Graph., 1997, pp. 271-296.
  21. K. Chinomi, N. Nitta, Y. Ito, and N. Babaguchi, ''PriSurv: Privacy pro- tected video surveillance system using adaptive visual abstraction,'' in Advances in Multimedia Modeling-MMM (Lecture Notes in Computer Science), vol. 4903, S. Satoh, F. Nack, and M. Etoh, Eds. Berlin, Germany: Springer, 2008, pp. 144-154.
  22. F. Dufaux, ''Video scrambling for privacy protection in video surveil- lance: Recent results and validation framework,'' Proc. SPIE vol. 8063, May 2011, Art. no. 806302.
  23. S. Çiftçi, A. O. Akyüz, and T. Ebrahimi, ''A reliable and reversible image privacy protection based on false colors,'' IEEE Trans. Multimedia, vol. 20, no. 1, pp. 68-81, Jan. 2018.
  24. V. E. Liong, J. Lu, Y.-P. Tan, and J. Zhou, ''Deep video hashing,'' IEEE Trans. Multimedia, vol. 19, no. 6, pp. 1209-1219, Jun. 2017.
  25. H. Hofbauer and A. Uhl, ''Identifying deficits of visual security metrics for images,'' Signal Process., Image Commun., vol. 46, pp. 60-75, Aug. 2016.
  26. M. N. Asghar, M. Ghanbari, M. Fleury, and M. J. Reed, ''Sufficient encryp- tion based on entropy coding syntax elements of H.264/SVC,'' Multimedia Tools Appl., vol. 74, no. 23, pp. 10215-10241, 2015.
  27. M. N. Asghar, R. Kousar, H. Majid, and M. Fleury, ''Transparent encryp- tion with scalable video communication: Lower-latency, CABAC-based schemes,'' J. Vis. Commun. Image Represent., vol. 45, pp. 122-136, May 2017.
  28. G. Alvarez and S. Li, ''Some basic cryptographic requirements for chaos-based cryptosystems,'' Int. J. Bifurcation Chaos, vol. 16, no. 8, pp. 2129-2151, 2006.
  29. M. N. Asghar, M. Ghanbari, M. Fleury, and M. J. Reed, ''Confidentiality of a selectively encrypted H.264 coded video bit-stream,'' J. Vis. Commun. Image Represent., vol. 25, no. 2, pp. 487-498, 2014.
  30. J. Daemen and V. Rijmen, The Design of Rijndael: AES-The Advanced Encryption Standard. Berlin, Germany: Springer, 2002.
  31. A. Shifa, M. N. Asghar, S. Noor, N. Gohar, and M. Fleury, ''Lightweight cipher for H.264 videos in the Internet of multimedia things with encryp- tion space ratio diagnostics,'' Sensors, vol. 19, no. 5, p. 1228, 2019.
  32. A. Senior, S. Pankanti, A. Hampapur, L. Brown, Y.-L. Tian, A. Ekin, J. Connell, C. F. Shu, and M. Lu, ''Enabling video privacy through computer vision,'' IEEE Security Privacy, vol. 3, no. 3, pp. 50-57, May 2005.
  33. T. Aste, P. Tasca, and T. D. Matteo, ''Blockchain technologies: The foresee- able impact on society and industry,'' Computer, vol. 50, no. 9, pp. 18-28, Jan. 2017.
  34. M. Liu, J. Shang, P. Liu, Y. Shi, and M. Wang, ''VideoChain: Trusted video surveillance based on blockchain for campus,'' in Cloud Computing and Security-ICCS (Lecture Notes in Computer Science), vol. 11066, X. Sun, Z. Pan, and E. Bertino, Eds. Cham, Switzerland: Springer, 2018, pp. 48-58.
  35. H. Vranken, ''Sustainability of bitcoin and blockchains,'' Current Opinion Environ. Sustainability, vol. 28, pp. 1-9, Oct. 2017.
  36. H. Al-Khateeb, G. Epiphaniou, and H. Daly, ''Blockchain for modern digi- tal Forensics: The chain-of-custody as a distributed ledger,'' in Blockchain and Clinical Trial (Advanced Sciences and Technologies for Security Applications), H. Jahankhani, S. Kendzierskyj, A. Jamal, G. Epiphaniou, and H. Al-Khateeb, Eds. Springer-Verlag, 2019.
  37. K. Wüst and A. Gervais, ''Do you need a Blockchain?'' in Proc. Crypto Valley Conf. Blockchain Technol., Jun. 2018, pp. 45-54.

Cited by

Sorted by citations

Authors
Asghar, M. N., Kanwal, N., Lee, B., Fleury, M., Herbst, M., & Qiao, Y.
Affiliations
  • Athlone Institute of Technology (IE)
  • University of Suffolk (GB)
Venue
IEEE Access
Published
2019
Volume
7
Pages
111709-111726
ISSN
2169-3536 (ISSN-L)
OpenAlex
W2967606168
Cited by
69
References
2
Citations by year
2026: 4 · 2025: 9 · 2024: 18 · 2023: 10 · 2022: 9 · 2021: 9 · 2020: 7 · 2019: 3
FWCI
61.09
Type
journal article
Language
en
Open access
Locations
  • IEEE Access (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Research@THEA (submittedVersion, cc-by)
Funders
  • Marie Skłodowska-Curie (MSC) Career-FIT Postdoc Fellowship (MF 2018-0179)
  • European Union’s Horizon2020 Research and Innovation Programme under the MSC (713654)
  • Science Foundation Ireland (SFI 16/RC/3918)
  • European Regional Development Fund
Topics
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
Keywords
General Data Protection Regulation, video surveillance, visual privacy, personal data protection, data protection by design, pseudonymization, encryption, blockchain, machine learning, computer vision, image processing, privacy compliance

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review