Frameworks For Private Identification Of Nearby Friends
Translated title
Frameworks For Privat Identifikation Af Nærved Venner
Authors
Thomsen, Jeppe Rishede ; Šikšnys, Laurynas
Term
2. term
Education
Publication year
2009
Pages
74
Abstract
Apps bruger i stigende grad GPS til at afgøre, om to brugere er tæt på hinanden, men many ønsker ikke at dele deres præcise placering. Denne afhandling præsenterer to nye klient-server-systemer, der finder nærhed uden at afsløre brugernes lokationer. Et centralt træk er blind evaluering af forespørgsler: serveren vurderer, om brugere er tæt på, ud fra krypterede data, uden adgang til de faktiske koordinater. Eksperimenter viser, at begge systemer kan skaleres til mange brugere og egner sig til anvendelse i praksis.
Apps increasingly use GPS to tell when two users are near each other, but many people do not want to share their exact locations. This thesis presents two new client-server frameworks that detect proximity while keeping locations private. A key feature is blind query evaluation: the server determines whether users are close by analyzing encrypted data, without seeing their actual coordinates. Experiments show both frameworks scale to large numbers of users and are suitable for real-world use.
[This abstract was generated with the help of AI]
Keywords
Mobile Clients ; Friend Locator ; Friend Finder ; Privacy Aware ; Proximity Detection ; Mobile social networks ; Grid based ; Privacy ; Anonymity ; Blind evaluation of queries ; Mobile Klienter ; Ven finder ; Ven Finder ; Nærved opdager ; mobile sociale netværk ; gitter baseret ; Anonymitet ; Blind evalution af forespørgelse
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