Feedback based dynamic trust model for secured communication in multi-agent systems

Abstract

Most network applications such as pervasive computing, grid computing, P2P etc. can be viewed as multi-agent systems which are open, anonymous and dynamic in nature. Due to such nature multiagent systems present potential threats in ensuring secured communication. One of the key feasible ways to minimize threats is to evaluate the trust and reputation of the interacting agents. Many trust models have done so, but they fail to properly evaluate trust when malicious agents behave in an unpredictable way. Besides that they are also ineffective in providing quick response to a malicious agent’s oscillating behavior, i.e., they are unable to assess the true nature of an opportunistic agent. To cope with the strategically altering behavior this thesis presents a dynamic trust model called SECTrust where we analyze the different factors related to the trust of an agent and then propose a comprehensive model for evaluating trust. In our trust model we have considered various factors in computing the trust of agents which includes recent trend, historical trend, sudden deviation of trust, confidence factor and decay of trust. We have also tuned our trust model for the different parameters that we have considered to get the best possible results. Simulations show that our model compared to other existing models can effectively cope with the strategic behavioral change of an agent and at the same time efficiently isolate the malicious ones. So, our trust model is more robust and effective in preventing attacks from opportunistic malicious agents and can thus ensure secured communication among the participating agents.