File System Support for Privacy-Preserving Analysis and Forensics in Low-Bandwidth Edge Environments

被引:4
|
作者
Ovesen, Aril Bernhard [1 ]
Nordmo, Tor-Arne Schmidt [1 ]
Johansen, Havard Dagenborg [1 ]
Riegler, Michael Alexander [1 ,2 ]
Halvorsen, Pal [2 ,3 ]
Johansen, Dag [1 ]
机构
[1] UiT Arctic Univ Norway, Dept Comp Sci, N-9037 Tromso, Norway
[2] SimulaMet, Holist Syst Dept, N-0164 Oslo, Norway
[3] Oslo Metropolitan Univ, Dept Comp Sci, N-0130 Oslo, Norway
关键词
edge computing; privacy preservation; artificial intelligence; file systems; machine learning; digital forensics; DIMENSION;
D O I
10.3390/info12100430
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.</p>
引用
收藏
页数:19
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