Understanding the effects of P2P dynamics on trust bootstrapping

  • Authors:
  • Marc SáNchez-Artigas;Blas Herrera

  • Affiliations:
  • Universitat Rovira i Virgili, Department of Computer Engineering and Maths, Av. Paisos Catalans 26, Tarragona, Spain;Universitat Rovira i Virgili, Department of Computer Engineering and Maths, Av. Paisos Catalans 26, Tarragona, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2013

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Abstract

Reputation and trust systems rely on historical information to account for uncertainty about the intention of users to cooperate. In open, dynamic systems like peer-to-peer (P2P) networks, however, forming trust relationships is often a lengthy and time consuming effort due to the anonymous and discontinuous participation of users. For example, the flow of transactions may be interrupted by unexpected user departures, precluding trustors from gaining the necessary experience to make an accurate trust evaluation. The problem is further complicated in the case that no previous direct and reputational evidence is available. This happens, for instance, when a new user joins the system for the first time or users form short-term, ad hoc groups around a shared goal, which is very common in P2P networks. In these cases, the problem is how to minimize the time to bootstrap trust between volatile users who are unknown to one another. To shed light on this question, this paper presents an accurate model for capturing the influence of churn - the continuous process of node arrival and departure - on trust bootstrapping. Using our analytical model, we show that churn can be very problematic in real P2P systems and develop equations that allow system architects to compute the minimal transaction rate that achieves quick bootstrapping of trust. Also, we present an example of how our analytical framework can be used to design a viable solution for the trust bootstrapping problem in dynamic settings. The core idea is that users ask their social links to transact with strangers and together generate trust evaluations in a short time scale. Finally, we verify our theoretical results by simulation and confirm how a simple application of our framework can reduce bootstrapping times by 50% in environments with high churn rates.