Skip to main content
SpringerLink
Log in

Sustainable Commercial Fishery Control Using Multimedia Forensics Data from Non-trusted, Mobile Edge Nodes

  • Conference paper
  • First Online:
MultiMedia Modeling (MMM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14556))

Included in the following conference series:

  • 366 Accesses

Abstract

Uncontrolled over-fishing has been exemplified by the UN as a serious ecological challenge and a major threat to sustainable food supplies. Emerging trends within governing bodies point towards digital solutions by deploying CCTV-based video monitoring systems on a large scale. We conjecture that such systems are not feasible when reliant on satellite broadband in remote areas, and expose workers aboard fishing vessels to unneeded manual surveillance. To facilitate this, we propose Dorvu, a AI-based multimedia distributed storage system designed for edge environments, with a specific focus on commercial fishery monitoring. Dorvu addresses the challenges of secure data storage, fault tolerance, availability, and remote access in hostile edge environments. The system employs a novel data distribution scheme involving sensor readings and AI video content extraction to ensure the preservation of forensic evidence even in unstable conditions. Experimental evaluations demonstrate the feasibility of real-time multimedia data collection, analysis, and distribution in networks of edge devices on-board active fishing vessels. Dorvu offers a practical alternative to current governmental surveillance trends that compromise data security and privacy, and we propose it as a solution for edge-based forensic data management in commercial fisheries and similar applications.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Dorvu is a Northern Sámi term, meaning security or trust.

References

  1. Alsile, J.A., et al.: Áika: a distributed edge system for AI inference. Big Data Cogn. Comput. 6(2), 68 (2022)

    Article  Google Scholar 

  2. Bhatnagar, N., Miller, E.L.: Designing a secure reliable file system for sensor networks. In: Proceedings of the 2007 ACM workshop on Storage security and survivability, pp. 19–24 (2007)

    Google Scholar 

  3. Bischof, H., Godec, M., Leistner, C., Rinner, B., Starzacher, A.: Autonomous audio-supported learning of visual classifiers for traffic monitoring. IEEE Intell. Syst. 25(3), 15–23 (2010)

    Article  Google Scholar 

  4. Conoscenti, M., Vetro, A., De Martin, J.C.: Blockchain for the internet of things: A systematic literature review. In: 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp. 1–6. IEEE (2016)

    Google Scholar 

  5. Costello, C.e.a.: The future of food from the sea. Nature (London) 588(7836), 95 (2020)

    Google Scholar 

  6. Fitwi, A., Chen, Y., Zhu, S.: Lightweight frame scrambling mechanisms for end-to-end privacy in edge smart surveillance. IET Smart Cities 4(1), 17–35 (2022)

    Article  Google Scholar 

  7. Fournier, M., Casey Hilliard, R., Rezaee, S., Pelot, R.: Past, present, and future of the satellite-based automatic identification system: Areas of applications (2004–2016). WMU J. Marit. Aff. 17, 311–345 (2018)

    Article  Google Scholar 

  8. Ghemawat, S., Gobioff, H., Leung, S.T.: The google file system. In: Proceedings of the 19th ACM symposium on Operating systems principles, pp. 29–43 (2003)

    Google Scholar 

  9. Gu, B., Wang, X., Qu, Y., Jin, J., Xiang, Y., Gao, L.: Context-aware privacy preservation in a hierarchical fog computing system. In: ICC 2019–2019 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2019)

    Google Scholar 

  10. Inc, I.C.: Iridium certus 200 datasheet. https://www.iridium.com/services/iridium-certus-200/ (2023). Accessed 8 Sept 2021

  11. Juels, A., Kaliski Jr, B.S.: Pors: Proofs of retrievability for large files. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, pp. 584–597 (2007)

    Google Scholar 

  12. Kim, G.H., Spafford, E.H.: The design and implementation of tripwire: a file system integrity checker. In: Proceedings of the 2nd ACM Conference on Computer and Communications Security, pp. 18–29 (1994)

    Google Scholar 

  13. Kuhl, J.G., Reddy, S.M.: Distributed fault-tolerance for large multiprocessor systems. In: Proceedings of the 7th Annual Symposium on Computer Architecture, pp. 23–30 (1980)

    Google Scholar 

  14. Martinussen, T.M.: Danske fiskere samler seg mot kameraovervåkning. Fiskeribladet (2020), https://www.fiskeribladet.no/nyheter/danske-fiskere-samler-seg-mot-kamera-overvakning-i-fiskeriene/2-1-839478. Accessed 5 Dec 2022

  15. Ministry of Trade: Industry and Fisheries: Framtidens fiskerikontroll. NOU 19, 21 (2019)

    Google Scholar 

  16. Muthitacharoen, A.: A low-bandwidth network file system. In: Proceedings of the 18th ACM Symposium on Operating Systems Principles, pp. 174–187 (2001)

    Google Scholar 

  17. Márcia Bizzotto: Fishing rules: Compulsory cctv for certain vessels to counter infractions. European Parliament Press Release (2021). https://www.europarl.europa.eu/news/en/press-room/20210304IPR99227/fishing-rules-compulsory-cctv-for-certain-vessels-to-counter-infractions

  18. Nordmo, T.A.S., Ovesen, A.B., Johansen, H.D., Riegler, M.A., Halvorsen, P., Johansen, D.: Dutkat: A multimedia system for catching illegal catchers in a privacy-preserving manner. In: Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval, pp. 57–61 (2021)

    Google Scholar 

  19. Nordmo, T.A.S.: Dutkat: a privacy-preserving system for automatic catch documentation and illegal activity detection in the fishing industry (2023)

    Google Scholar 

  20. Nordmo, T.A.S., et al.: Njord: a fishing trawler dataset. In: Proceedings of the 13th ACM Multimedia Systems Conference, pp. 197–202 (2022)

    Google Scholar 

  21. Ovesen, A.B., Nordmo, T.A.S., Johansen, H.D., Riegler, M.A., Halvorsen, P., Johansen, D.: File system support for privacy-preserving analysis and forensics in low-bandwidth edge environments. Information 12(10), 430 (2021)

    Article  Google Scholar 

  22. for Primary Industries, M.: On-board cameras for commercial fishing vessels (2023), https://www.mpi.govt.nz/fishing-aquaculture/commercial-fishing/fisheries-change-programme/on-board-cameras-for-commercial-fishing-vessels/ Accessed 20 Nov 2022

  23. Rajagopalan, R., Varshney, P.K.: Data aggregation techniques in sensor networks: a survey (2006)

    Google Scholar 

  24. Sodagar, I.: The mpeg-dash standard for multimedia streaming over the internet. IEEE Multimedia 18(4), 62–67 (2011)

    Article  Google Scholar 

  25. Solberg, R.R.: Bærekraftig fiskeri, governance og tid. Master’s thesis, The University of Bergen (2022)

    Google Scholar 

  26. Sumaila, U.R., Tai, T.C.: End overfishing and increase the resilience of the ocean to climate change. Front. Mar. Sci. 7, 523 (2020)

    Article  Google Scholar 

  27. Tarasov, V., Gupta, A., Sourav, K., Trehan, S., Zadok, E.: Terra incognita: on the practicality of user-space file systems. In: 7th \(\{\)USENIX\(\}\) Workshop on Hot Topics in Storage and File Systems (HotStorage 15) (2015)

    Google Scholar 

  28. Tornsberg, L.: Danske pelagiske fiskere indfører 100% dokumenteret fiskeri. Fiskerforum (2022), https://fiskerforum.dk/danske-pelagiske-fiskere-indfoerer-100-dokumenteret-fiskeri-%E2%80%A8/ Accessed 15 Jan 2023

  29. UNODC: Fisheries crime: transnational organized criminal activities in the context of the fisheries sector (2016)

    Google Scholar 

  30. Wang, Q., Ren, K., Yu, S., Lou, W.: Dependable and secure sensor data storage with dynamic integrity assurance. ACM Trans. Sensor Netw. (TOSN) 8(1), 1–24 (2011)

    Google Scholar 

  31. Weil, S.A., Brandt, S.A., Miller, E.L., Maltzahn, C.: Crush: Controlled, scalable, decentralized placement of replicated data. In: Proceedings of the 2006 ACM/IEEE conference on Supercomputing, pp. 122-es (2006)

    Google Scholar 

  32. Winkler, T., Rinner, B.: Security and privacy protection in visual sensor networks: a survey. ACM Comput. Surv. (CSUR) 47(1), 1–42 (2014)

    Article  Google Scholar 

  33. Xu, M., Xu, W., O’Kane, J.: Content-aware data dissemination for enhancing privacy and availability in wireless sensor networks. In: 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, pp. 361–370. IEEE (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. UiT The Arctic University of Norway, Tromsø, Norway

    Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Michael Alexander Riegler & Dag Johansen

  2. Simula Metropolitan Center for Digital Engineering, Oslo, Norway

    Michael Alexander Riegler & Pål Halvorsen

  3. Oslo Metropolitan University, Oslo, Norway

    Michael Alexander Riegler & Pål Halvorsen

Authors
  1. Aril Bernhard Ovesen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tor-Arne Schmidt Nordmo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael Alexander Riegler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pål Halvorsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dag Johansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aril Bernhard Ovesen .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Stevan Rudinac

  2. Delft University of Technology, Delft, The Netherlands

    Alan Hanjalic

  3. Delft University of Technology, Delft, The Netherlands

    Cynthia Liem

  4. University of Amsterdam, Amsterdam, The Netherlands

    Marcel Worring

  5. Reykjavik University, Reykjavik, Iceland

    Björn Þór Jónsson

  6. Microsoft Research Lab – Asia, Beijing, China

    Bei Liu

  7. The University of Tokyo, Tokyo, Japan

    Yoko Yamakata

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ovesen, A.B., Nordmo, TA.S., Riegler, M.A., Halvorsen, P., Johansen, D. (2024). Sustainable Commercial Fishery Control Using Multimedia Forensics Data from Non-trusted, Mobile Edge Nodes. In: Rudinac, S., et al. MultiMedia Modeling. MMM 2024. Lecture Notes in Computer Science, vol 14556. Springer, Cham. https://doi.org/10.1007/978-3-031-53311-2_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-53311-2_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53310-5

  • Online ISBN: 978-3-031-53311-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation