Pregled bibliografske jedinice broj: 1280137
Data Analysis using Privacy-Preserving Methods
Data Analysis using Privacy-Preserving Methods // Baška SIF Forum 2023
Baška, Hrvatska, 2023. (predavanje, recenziran, neobjavljeni rad, znanstveni)
CROSBI ID: 1280137 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Data Analysis using Privacy-Preserving Methods
Autori
Banov, Marina
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni
Skup
Baška SIF Forum 2023
Mjesto i datum
Baška, Hrvatska, 11.06.2023. - 15.06.2023
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Recenziran
Ključne riječi
privacy ; secure multi-party computation ; spatial data analysis
Sažetak
Sharing data and communicating our knowledge to others has been essential for the development of human culture, but in certain situations, the need to keep information private can interfere with the desire to collaboratively reach an agreement. Modern data privacy laws discourage systems that heavily rely on the third party's ethical integrity. To ensure secure and reliable data sharing, a distributed system capable of computing functions over data in a manner that preserves privacy emerged in the 1980s, called Secure Multi-Party Computation (SMPC). SMPC guarantees that anything a party or a sufficiently small coalition of parties sees during the protocol can only be deduced from their inputs and outputs. The purpose of this paper is to explore this field, the concepts surrounding it, and its possible applications, with focus on spatial data analysis.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
