1,071 research outputs found
How Far Removed Are You? Scalable Privacy-Preserving Estimation of Social Path Length with Social PaL
Social relationships are a natural basis on which humans make trust
decisions. Online Social Networks (OSNs) are increasingly often used to let
users base trust decisions on the existence and the strength of social
relationships. While most OSNs allow users to discover the length of the social
path to other users, they do so in a centralized way, thus requiring them to
rely on the service provider and reveal their interest in each other. This
paper presents Social PaL, a system supporting the privacy-preserving discovery
of arbitrary-length social paths between any two social network users. We
overcome the bootstrapping problem encountered in all related prior work,
demonstrating that Social PaL allows its users to find all paths of length two
and to discover a significant fraction of longer paths, even when only a small
fraction of OSN users is in the Social PaL system - e.g., discovering 70% of
all paths with only 40% of the users. We implement Social PaL using a scalable
server-side architecture and a modular Android client library, allowing
developers to seamlessly integrate it into their apps.Comment: A preliminary version of this paper appears in ACM WiSec 2015. This
is the full versio
Enabling Social Applications via Decentralized Social Data Management
An unprecedented information wealth produced by online social networks,
further augmented by location/collocation data, is currently fragmented across
different proprietary services. Combined, it can accurately represent the
social world and enable novel socially-aware applications. We present
Prometheus, a socially-aware peer-to-peer service that collects social
information from multiple sources into a multigraph managed in a decentralized
fashion on user-contributed nodes, and exposes it through an interface
implementing non-trivial social inferences while complying with user-defined
access policies. Simulations and experiments on PlanetLab with emulated
application workloads show the system exhibits good end-to-end response time,
low communication overhead and resilience to malicious attacks.Comment: 27 pages, single ACM column, 9 figures, accepted in Special Issue of
Foundations of Social Computing, ACM Transactions on Internet Technolog
WARP: A ICN architecture for social data
Social network companies maintain complete visibility and ownership of the
data they store. However users should be able to maintain full control over
their content. For this purpose, we propose WARP, an architecture based upon
Information-Centric Networking (ICN) designs, which expands the scope of the
ICN architecture beyond media distribution, to provide data control in social
networks. The benefit of our solution lies in the lightweight nature of the
protocol and in its layered design. With WARP, data distribution and access
policies are enforced on the user side. Data can still be replicated in an ICN
fashion but we introduce control channels, named \textit{thread updates}, which
ensures that the access to the data is always updated to the latest control
policy. WARP decentralizes the social network but still offers APIs so that
social network providers can build products and business models on top of WARP.
Social applications run directly on the user's device and store their data on
the user's \textit{butler} that takes care of encryption and distribution.
Moreover, users can still rely on third parties to have high-availability
without renouncing their privacy
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