TY  - CONF
AU  - Stach, Christoph
AU  - Gritti, Clémentine
AU  - Przytarski, Dennis
AU  - Mitschang, Bernhard
A2  - Julien, Christine
A2  - Nurmi, Petteri
A2  - Zheng, James Xi
T1  - Trustworthy, Secure, and Privacy-aware Food Monitoring Enabled by Blockchains and the IoT
T2  - Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops
PB  - IEEE
AD  - Austin
Y1  - 2020/march
SP  - 50:1
EP  - 50:4
M3  - https://doi.org/10.1109/PerComWorkshops48775.2020.9156150
KW  - attribute-based credentials; blockchain; data authentication; IoT; privacy; service utility; transparency; trust
N2  - A large number of food scandals (e.g., falsely declared meat or non-compliance with hygiene regulations) are causing considerable concern to consumers. Although Internet of Things (IoT) technologies are used in the food industry to monitor production (e.g., for tracing the origin of meat or monitoring cold chains), the gathered data are not used to provide full transparency to the consumer. To achieve this, however, three aspects must be considered: a) The origin of the data must be verifiable, i.e., it must be ensured that the data originate from calibrated sensors. b) The data must be stored tamper-resistant, immutable, and open to all consumers. c) Despite this openness, the privacy of affected data subjects (e.g., the carriers) must still be protected. To this end, we introduce the SHEEPDOG architecture that "shepherds" products from production to purchase to enable a trustworthy, secure, and privacy-aware food monitoring. In SHEEPDOG, attribute-based credentials ensure trustworthy data acquisition, blockchain technologies provide secure data storage, and fine-grained access control enables privacy-aware data provision.
ER  -