Privacy-Aware personal Information Discovery model based on the cloud

Data collection, storage and manipulation have become more critical due to the growth of magnitude of their misuse or mismanagement impact in business and political scenarios nowadays. While research has pushed technology to deliver more powerful information discovery algorithms, and responsive on-demanding storage and processing capacity through data analysis and distributed cloud infrastructure, concerns about privacy have globally raised several discussions involving different sectors of the society. In particular, individual rights are highly impacted by privacy issues due to nowadays geographic distribution of sensitive information and its discovery. In this work, we present a model for privacy awareness during the data analytics process in a context of scalable computing using the cloud. Our approach addresses privacy issues both in data analytics process and in the infrastructure resource allocation according to privacy regulation in Service Level Agreements (SLA). The proposed model for Privacy-Aware Information Discovery (PAID-M) provides privacy awareness by executing data analytics algorithms encapsulated with privacy preserving techniques. The model also presents how it intends to address the privacy issue in the cloud deployment process by considering differences in privacy regulations and jurisdictions.