A reliable path between target users and clients in social networks using an inverted ant colony optimization algorithm

Internet has become an integral section of human life. Millions of people are joining online social networks every day, interacting with others whom they did not know already. Establishing trust among those indirectly connected users performs a crucial role in improving the quality of social network services and creating the security for them. Nowadays, there are many paths between clients (service requesters) and target users (service providers) in online social networks. Among existing paths finding a trust path for trustworthy services is a vital job. Also, in many previous methods, such as ant colony optimization algorithm (ACO) load balancing among target users is inefficient. Therefore, in this paper we propose an inverted ant colony optimization algorithm to find a reliable path along with improving load balancing among the target users. The inverted ant colony optimization algorithm is a diversity of the basic ant colony optimization algorithm in which, the updated pheromone has a reverse effect on the selected path by the ants. Finally, we simulate the proposed method by using the original experimental dataset and evaluate the proposed method in terms of load balancing, waiting time and execution time in comparison with the ant colony optimization algorithm. The obtained results are very promising.