How can we design a cost-effective model that ensures a high level of data integrity protection?

Everyone agree that data is more secured locally than when it is outsourced far away from their owners. But the growth of local data annually implies extra charges for the customers, which makes their business slowing down. Cloud computing paradigm comes with new technologies that offer a very economic and cost-effective solutions, but at the expense of security. So designing a lightweight system that can achieve a balance between cost and data security is really important. Several schemes and techniques has been proposed for securing, checking and repairing data, but unfortunately the majority doesn't respect and preserve the cost efficiency and profitability of cloud offers. In this paper we try to answer the question: how can we design a model that enables a high level of integrity check while preserving a minimum cost? We try also to analyze a new threat model regards the tracking of a file's fragments during a repair or a download operation, which can cause the total loss of customers data. The solution given in this paper is based on redistributing fragments locations after every data operation using a set of random values generated by a chaotic map. Finally, we provide a data loss insurance (data corruption as well) approach based on user estimation of data importance level that helps in reducing user concerns about data loss.