This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-05-01 Creation time: 23-38-56 --- Number of references 1 inproceedings 2019-dahlmanns-icnp-knowledgeSystem Privacy-Preserving Remote Knowledge System 2019 10 7 More and more traditional services, such as malware detectors or collaboration services in industrial scenarios, move to the cloud. However, this behavior poses a risk for the privacy of clients since these services are able to generate profiles containing very sensitive information, e.g., vulnerability information or collaboration partners. Hence, a rising need for protocols that enable clients to obtain knowledge without revealing their requests exists. To address this issue, we propose a protocol that enables clients (i) to query large cloud-based knowledge systems in a privacy-preserving manner using Private Set Intersection and (ii) to subsequently obtain individual knowledge items without leaking the client’s requests via few Oblivious Transfers. With our preliminary design, we allow clients to save a significant amount of time in comparison to performing Oblivious Transfers only. Poster Session private query protocol; knowledge system; remote knowledge; private set intersection; oblivious transfer kimusin; internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-dahlmanns-knowledge-system.pdf IEEE Proceedings of the 27th IEEE International Conference on Network Protocols (ICNP '19), October 7-10, 2019, Chicago, IL, USA Chicago, IL, USA 27th IEEE International Conference on Network Protocols (ICNP 2019) 7-10. Oct. 2019 978-1-7281-2700-2 2643-3303 10.1109/ICNP.2019.8888121 1 MarkusDahlmanns ChrisDax RomanMatzutt JanPennekamp JensHiller KlausWehrle