The Effectiveness of Reputation-Based Voting for Collusion Tolerance in Large-Scale Grids

Large scale grids permit to share grid resources spread over different autonomous administrative sites in the internet. The rapid progress of grid systems opens the door for numerous companies to adopt this technology in their business development. This progress is characterized by the increasing openness and opportunity of resource-sharing across organizations in different domains. In the business context, these shared resources can be misused by some malicious users that can abuse the provided resources and make them behave maliciously to return wrong results and sabotage the jobs execution. The common technique used by most grid systems to deal with this problem is based on replication with voting. Nevertheless, these techniques rely on the assumption that the grid resources behave independently. They may be ineffective where a number of collusive resources collectively return the same wrong results of a job execution. In order to overcome this threat, we propose a reputation-based voting (RBV) approach, which investigates the trustworthiness of the grid resources through a reputation system, and then takes a decision about the results. In addition, the performance of our approach and other voting techniques, like m-first voting and credibility-based voting, are evaluated through simulation to perceive the effect of collusive grid resources on the correctness of the results. The obtained results show that our approach achieves a lower error-rate and better performance in terms of overhead.