Date of Graduation
Master of Science in Computer Science (MS)
Computer Science & Computer Engineering
Second Committee Member
Cloud computing, Database, Security
Cloud computing offers a considerable number of advantages to clients and organizations that use several capabilities to store sensitive data, interact with applications, or use technology infrastructure to perform daily activities. The development of new models in cloud computing brings with it a series of elements that must be considered by companies, particularly when the sensitive data needs to be protected. There are some concerns related to security that need to be taken into consideration when a service provider manage and store the data in a location outside the company. In this research, a model that uses a trusted third party (TPP) to enforce the database security in the cloud is proposed. The model describes how a client processes a query securely by using encryption mechanisms and partitioning methods. The client establishes the communication with the TPP to retrieve the data from a cloud storage service. The TPP has two primary functions. First, perform a partition process over the data by using an index from one of the attributes in the table. As a result, the TPP sends to the cloud server the records in encrypted format with an index. Second, the TPP analyzes the client query to retrieve a segment of the data from the cloud based on the query conditions. The final result is submitted to the client in which a minimum workload is executed. Some simulations were performed to evaluate the efficiency of the model by using two partition techniques: Histogram based and Mondrian or Bisection Tree based partition. The strategy of the model is to process as much of the work at the TPP site and securely transmit the result. Using encrypted record in the cloud storage service prevents the provider to have any knowledge about the data and enforces the security of the database.
Fuentes Tello, V. (2017). Enforcing database security on cloud using a trusted third party based model. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/2438