With the mushroom growth of Cloud Service Providers (CSPs) offering services of similar functionality, makes a challenge for cloud users to choose an appropriate service provider from cloud marketplace. This unique paradigm brings about new risk related issues in Cloud Computing (CC) environment. This is because it is indispensable from a customer’s aspect to establish trust with a CSP with high risk of outsourced data to be misused. Though trustworthiness and competence to estimate risk of interaction and risk for customer’s privacy were addressed in many research works, the way through which the risk of outsourced data/ file can be minimized in the presence of malicious service providers pose challenging issues. The challenging issue of handling risk in cloud environment is addressed in this work through Risk Evaluation using Nash Equilibrium-based Bi-Matrix Decision (RE-NEBMD) model. RE-NEBMD model studies the problem of ensuring security where the possible risk of outsourced data is brought to an absolute minimum in Cloud Computing in the presence of malicious CSPs. Nash Equilibrium-based Trust Evaluation model performs trust evaluation model on CSPs for outsourced data based on strategy and utility function. Next, risk evaluation is measured using Bi-Matrix Decision model on the evaluated trust and risk is measured accordingly. Extensive analytical and experimental results are presented which show minimized cost during risk analysis, computation overhead and improving true positive rate or detected threats of our proposed model. © 2005 – 2016 JATIT & LLS. All rights reserved.