LiFTinG: Lightweight Freerider-Tracking in Gossip?

Abstract. This paper presents LiFTinG, the first protocol to detect freeriders, including colluding ones, in gossip-based content dissemina-tion systems with asymmetric data exchanges. LiFTinG relies on nodes tracking abnormal behaviors by cross-checking the history of their pre-vious interactions, and exploits the fact that nodes pick neighbors at random to prevent colluding nodes from covering up each others ’ bad actions. We present a methodology to set the parameters of LiFTinG based on a theoretical analysis. In addition to simulations, we report on the deploy-ment of LiFTinG on PlanetLab. In a 300-node system, where a stream of 674 kbps is broadcast, LiFTinG incurs a maximum overhead of only 8 % while providing good results: for instance, with 10 % of freeriders de-creasing their contribution by 30%, LiFTinG detects 86 % of the freeriders after only 30 seconds and wrongfully expels only a few honest nodes.