Big Data: diretrizes e técnicas para preservação da privacidade

• Ano de defesa: 2016
• Autor(a) principal: Licks, Rogério Augusto de Souza
• Orientador(a): Guadagnin, Renato da Veiga
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Católica de Brasília
• Programa de Pós-Graduação: Programa Strictu Sensu em Gestão do Conhecimento e da Tecnologia da Informação
• Departamento: Escola de Educação, Tecnologia e Comunicação
• País: Brasil
• Palavras-chave em Português: Tecnologia da informação; Big Data; Privacidade; Diretrizes; Técnicas; Gestão do Conhecimento
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://bdtd.ucb.br:8443/jspui/handle/tede/1972

Success in business requires understanding and application of innovative strategic and business solutions geared to the customer with the use of competitive and strategic intelligence, based on information and knowledge for adequate and agile decision support. Big Data is a powerful tool to achieve these goals. The value provided by this approach considers the improvement of products and services, operational efficiency, increased production, overcoming the competition, resulting in offering best solutions for customers issues in a satisfactory and differentiated way. This work intends to present guidelines and techniques concerning privacy preserving in the use of Big Data. Business success strongly depends on how organizations deal with policies linked to storing personal data from its customers, and how they keep a balance between getting value and assuring the citizens right to control exposure and availability of their own data. A qualitative and bibliographic approach was used as a research method through literature review of issues Big Data and privacy. The results confirmed the existence of guidelines represented by laws and regulations applied in Europe, USA, Asia, as well as techniques for preserving privacy, such as the anonymisation of data and differential privacy, including application to Big Data. As future study concerning the definition of property rights and privacy, new approaches on business models that involve Internet of Things can be developed.