International audienceWe address the polling problem in social networks where users want to preserve the confidentiality of their votes, obtain the correct final result, and hide, if any, their misbehaviors. Guerraoui et al. [15, 16] recently proposed polling protocols that neither rely on any central authority nor cryptography system. However, these protocols can be deployed safely and efficiently provided that the social graph structure should be transformed into a ring structure-based overlay and the number of participating users is a perfect square. Consequently, designing secure and efficient polling protocols regardless these constraints remains a challenging issue.In this paper, we present EPol, a simple decentralized polling protocol that is deployed on more general social graphs. More explicitly, we define a family of social graphs that satisfy what we call the m-broadcasting property (where m is not greater than the minimum node degree) and show their structures enable low communication cost and constitute necessary and sufficient condition to ensure vote privacy and limit the impact of dishonest users on the accuracy of the polling output. EPol is effective to compute more precisely the final result and the communication and spatial complexities are close to be linear

We tackle the polling problem in social networks where the privacy of exchanged information and user reputation are very critical. Indeed, users want to preserve the confidentiality of their votes and to hide, if any, their misbehaviors. Recent works [9,10] proposed polling protocols based on simple secret sharing scheme and without requiring any central authority or cryptography system. But these protocols can be deployed safely provided that the social graph structure should be transformed into a ring-based structure and the number of participating users is perfect square. Accordingly, devising polling protocols regardless these constraints remains a challenging issue. In this work, we propose a simple decentralized polling protocol that relies on the current state of social graphs. More explicitly, we define one family of social graphs and show their structures constitute necessary and sufficient condition to ensure vote privacy and limit the impact of dishonest users on the accuracy of the output of the poll. In a system of N users with D ≤ N/5 dishonest ones (and similarly to the works [9,10] where they considered D < √ N ), a privacy parameter k enables us to obtain the following results: (i) the probability to recover one vote of honest node is bounded by 2k m=k+1 D N m . 1 2 2k+1−m ; (ii) the maximum number of votes revealed by dishonest nodes is 2D; and, (iii) the maximum impact on the output is (6k + 4)D. Despite the use of richer social graph structures, we succeed to detect the misbehaving users by manipulating verification procedures based on shortest path scheme and routing tables. An experimental evaluation demonstrates that the dishonest coalition never affects the outcome of the poll outside the theoretical bound of (6k + 4)D.

International audienceOnline social networks are currently experiencing a peak and they resemble real platforms of social conversion and content delivery. Indeed, they are exploited in many ways: from conducting public opinion polls about any political issue to planning big social events for a large public. To securely perform these large-scale computations, current protocols use a simple secret sharing scheme which enables users to obfuscate their inputs. However, these protocols require a minimum number of friends, i.e. the minimum degree of the social graph should be not smaller than a given threshold. Often this condition is not satisfied by all social graphs. Yet we can reuse these graphs after some structural modifications consisting in adding new friendship relations. In this paper, we provide the first definition and theoretical analysis of the ''\emph{adding friends}'' problem. We formally describe this problem that, given a graph $G$ and parameter $c$, asks for the graph satisfying the threshold $c$ that results from $G$ with the minimum of edge-addition operations. We present algorithms for solving this problem in centralized social networks. An experimental evaluation on real-world social graphs demonstrates that our protocols are accurate and inside the theoretical bounds

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