CAN't - An ISOBUS Privacy Proxy for Collaborative Smart Farming

Autor(en): Helmke, R.
Bauer, J.
Bothe, A. 
Aschenbruck, N. 
Stichwörter: Agricultural machinery; Agriculture; Computer hardware description languages; Control system synthesis; Controller Area Network; Controllers; Data Sovereignty; Data streams; ISO11783; ISOBUS; Privacy; Process control, Controller area network; Smart Farming; Smart Farming, Data privacy
Erscheinungsdatum: 2019
Herausgeber: Institute of Electrical and Electronics Engineers Inc.
Journal: 2019 IEEE 38th International Performance Computing and Communications Conference, IPCCC 2019
Zusammenfassung: 
Smart Farming is driven by the emergence of precise positioning systems and Internet of Things technologies which have already enabled site-specific applications, a sustainable resource management, and interconnected machinery. Nowadays, agricultural machines and implements are equipped with multiple embedded sensors and actors continuously producing extensive data streams. For data communication on such machinery, ISOBUS, an internal vehicle bus, is used. ISOBUS is based on the machine's Controller Area Network(CAN). However, neither CAN nor ISOBUS communication takes privacy or data sovereignty issues into account. With increasing interconnectivity of agricultural machines and their integration into farm management systems, those issues become more and more serious. In this paper, we briefly present the architecture of our modular privacy framework CAN't. Using off-the-shelf hardware, a special proxy is prototypically implemented that allows to purposefully filter and manipulate CAN data streams for the sake of privacy. The feasibility and possibilities of our approach are described in this paper. By means of a customized video game, a live demonstration will additionally show the effect of the proposed privacy filters. © 2019 IEEE.
Beschreibung: 
Conference of 38th IEEE International Performance Computing and Communications Conference, IPCCC 2019 ; Conference Date: 29 October 2019 Through 31 October 2019; Conference Code:156922
ISBN: 9781728110257
DOI: 10.1109/IPCCC47392.2019.8958765
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079097419&doi=10.1109%2fIPCCC47392.2019.8958765&partnerID=40&md5=da7d80ddbe8057984f9d4441ea274671

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