File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments
In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of co...
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Online Access: | https://hdl.handle.net/11250/2978618 https://doi.org/10.3390/info12100430 |
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fthsosloakersoda:oai:oda.oslomet.no:11250/2978618 2023-05-15T15:06:20+02:00 File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments Ovesen, Aril Bernhard Nordmo, Tor-Arne Schmidt Johansen, Håvard D. Riegler, Michael Alexander Halvorsen, Pål Johansen, Dag 2021-10-21T11:39:36Z application/pdf https://hdl.handle.net/11250/2978618 https://doi.org/10.3390/info12100430 eng eng MDPI Information;Volume 12, Issue 10 Norges forskningsråd: 263248 Norges forskningsråd: 274451 urn:issn:2078-2489 https://hdl.handle.net/11250/2978618 https://doi.org/10.3390/info12100430 cristin:1947539 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no © 2021 by the authors. CC-BY 430 Information 12 10 1-19 Edge computing Privacy preservation Artificial intelligence File systems Machine learning Digital forensics VDP::Informasjons- og kommunikasjonssystemer: 321 VDP::Information and communication systems: 321 Peer reviewed Journal article 2021 fthsosloakersoda https://doi.org/10.3390/info12100430 2022-02-16T23:34:22Z In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of commercial fishery surveillance operations. This is in response to potentially privacy-infringing mandates from some governments to combat overfishing and other sustainability challenges. Our approach is to deploy sensory devices and distributed artificial intelligence algorithms on mobile, offshore fishing vessels and at mainland central control centers. To facilitate this, we need a novel data plane supporting efficient, available, secure, tamper-proof, and compliant data management in this weakly connected offshore environment. We have built our first prototype of Dorvu, a novel distributed file system in this context. Our devised architecture, the design trade-offs among conflicting properties, and our initial experiences are further detailed in this paper. This work is partially funded by the Research Council of Norway project numbers 274451 and 263248, and Lab Nord-Norge (“Samfunnsløftet”). publishedVersion Article in Journal/Newspaper Arctic Arctic Ocean Nord-Norge OsloMet (Oslo Metropolitan University): ODA (Open Digital Archive) Arctic Arctic Ocean Norway Information 12 10 430 |
institution |
Open Polar |
collection |
OsloMet (Oslo Metropolitan University): ODA (Open Digital Archive) |
op_collection_id |
fthsosloakersoda |
language |
English |
topic |
Edge computing Privacy preservation Artificial intelligence File systems Machine learning Digital forensics VDP::Informasjons- og kommunikasjonssystemer: 321 VDP::Information and communication systems: 321 |
spellingShingle |
Edge computing Privacy preservation Artificial intelligence File systems Machine learning Digital forensics VDP::Informasjons- og kommunikasjonssystemer: 321 VDP::Information and communication systems: 321 Ovesen, Aril Bernhard Nordmo, Tor-Arne Schmidt Johansen, Håvard D. Riegler, Michael Alexander Halvorsen, Pål Johansen, Dag File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
topic_facet |
Edge computing Privacy preservation Artificial intelligence File systems Machine learning Digital forensics VDP::Informasjons- og kommunikasjonssystemer: 321 VDP::Information and communication systems: 321 |
description |
In this paper, we present initial results from our distributed edge systems research in the domain of sustainable harvesting of common good resources in the Arctic Ocean. Specifically, we are developing a digital platform for real-time privacy-preserving sustainability management in the domain of commercial fishery surveillance operations. This is in response to potentially privacy-infringing mandates from some governments to combat overfishing and other sustainability challenges. Our approach is to deploy sensory devices and distributed artificial intelligence algorithms on mobile, offshore fishing vessels and at mainland central control centers. To facilitate this, we need a novel data plane supporting efficient, available, secure, tamper-proof, and compliant data management in this weakly connected offshore environment. We have built our first prototype of Dorvu, a novel distributed file system in this context. Our devised architecture, the design trade-offs among conflicting properties, and our initial experiences are further detailed in this paper. This work is partially funded by the Research Council of Norway project numbers 274451 and 263248, and Lab Nord-Norge (“Samfunnsløftet”). publishedVersion |
format |
Article in Journal/Newspaper |
author |
Ovesen, Aril Bernhard Nordmo, Tor-Arne Schmidt Johansen, Håvard D. Riegler, Michael Alexander Halvorsen, Pål Johansen, Dag |
author_facet |
Ovesen, Aril Bernhard Nordmo, Tor-Arne Schmidt Johansen, Håvard D. Riegler, Michael Alexander Halvorsen, Pål Johansen, Dag |
author_sort |
Ovesen, Aril Bernhard |
title |
File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
title_short |
File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
title_full |
File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
title_fullStr |
File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
title_full_unstemmed |
File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments |
title_sort |
file system support for privacy-preserving analysis and forensics in low-bandwidth edge environments |
publisher |
MDPI |
publishDate |
2021 |
url |
https://hdl.handle.net/11250/2978618 https://doi.org/10.3390/info12100430 |
geographic |
Arctic Arctic Ocean Norway |
geographic_facet |
Arctic Arctic Ocean Norway |
genre |
Arctic Arctic Ocean Nord-Norge |
genre_facet |
Arctic Arctic Ocean Nord-Norge |
op_source |
430 Information 12 10 1-19 |
op_relation |
Information;Volume 12, Issue 10 Norges forskningsråd: 263248 Norges forskningsråd: 274451 urn:issn:2078-2489 https://hdl.handle.net/11250/2978618 https://doi.org/10.3390/info12100430 cristin:1947539 |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no © 2021 by the authors. |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3390/info12100430 |
container_title |
Information |
container_volume |
12 |
container_issue |
10 |
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430 |
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1766337960072970240 |