Privacy-Preserving Association Rule Mining in Distributed Database Environment: A Review

Abstract

AbstractThe research in this paper analyzes the origin of the data generated and treated as Big Data and discusses the hypothesis about the conflict generated by the management of personal data privacy. It is based on a model to identify the set of management practices and resources, resulting from the integration of guidelines, norms, standards and contractual commitments that are more relevant to keeping personal data safe and generating trust in the environment. The field study shows the importance and urgency of this issue, given that it is necessary to innovate in business management, the provision of public services and the design and implementation of regional development policies. Through its conclusions, it is verified that an intelligent management is needed to rectify the course in terms of discovering and detecting patterns, relations and formulating models from these gigantic databases. This work presents a generic model for the management of privacy in the cloud of huge volumes of data. The impact of privacy is analyzed, risks are identified, and solutions provided by standards are explored to develop controls that can be integrated into a model to establish the steps so that any type of public or private organization can verify the organizational impact of its products, processes or service in the fulfillment of its strategic objectives.KeywordsBig DataStandardsDatabase and large data managementData modelsData privacySecurity