Abstract: A system and method for detecting fake accounts in OSNs is proposed to aid the OSN provider 20 against fake users, wherein a social graph G of the OSN, with n nodes, a non-Sybil region GH and a Sybil region GS, is obtained and the following steps are performed: a trust value T(i)(v) is computed through i power iterations on each node v of the social graph G, i=0, 1, . . . O(log n) the power iterations distribute the trust value T(i)(v) from each node v to its neighbor nodes, after O(log n) power iterations, ranking nodes by a degree-normalized trust T ^ v = T ( w ) ? ( v ) deg ? ( v ) in order to obtain a ranked list of nodes, detecting fake accounts based on the obtained ranked list assigning intervals in the ranked list to a fake portion, determined by manual inspection means of the OSN provider, based on the degree-normalized trust of the nodes belonging to the intervals.

Abstract: A system and method for detecting fake accounts in OSNs is proposed to aid the OSN provider 20 against fake users, wherein a social graph G of the OSN, with n nodes, a non-Sybil region GH and a Sybil region GS, is obtained and the following steps are performed: a trust value T(i)(v) is computed through i power iterations on each node v of the social graph G, i=0, 1, . . . O(log n) the power iterations distribute the trust value T(i)(v) from each node v to its neighbour nodes, after O(log n) power iterations, ranking nodes by a degree-normalized trust T ^ v = T ( w ) ? ( v ) deg ? ( v ) in order to obtain a ranked list of nodes, detecting fake accounts based on the obtained ranked list assigning intervals in the ranked list to a fake portion, determined by manual inspection means of the OSN provider, based on the degree-normalized trust of the nodes belonging to the intervals.