Emerging Technologies in a Modern Competitive Scenario: Understanding the Panorama for Security and Privacy Requirements

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Author(s): George Leal Jamil (Informações em Rede Consultoria e Treinamento Ltda, Brazil)and Alexis Rocha da Silva (IBM Software Engineering, Brazil)
Copyright: 2021
Pages: 16
Source title: Handbook of Research on Digital Transformation and Challenges to Data Security and Privacy
Source Author(s)/Editor(s): Pedro Fernandes Anunciação (Polytechnic Institute of Setúbal, Portugal), Cláudio Roberto Magalhães Pessoa (Escola de Engenharia de Minas Gerais, Brazil)and George Leal Jamil (Informações em Rede Consultoria e Treinamento, Brazil)
DOI: 10.4018/978-1-7998-4201-9.ch001

Keywords: Cyber and Network Security / Information Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

Users' personal, highly sensitive data such as photos and voice recordings are kept indefinitely by the companies that collect it. Users can neither delete nor restrict the purposes for which it is used. Learning how to machine learning that protects privacy, we can make a huge difference in solving many social issues like curing disease, etc. Deep neural networks are susceptible to various inference attacks as they remember information about their training data. In this chapter, the authors introduce differential privacy, which ensures that different kinds of statistical analysis don't compromise privacy and federated learning, training a machine learning model on a data to which we do not have access to.

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Emerging Technologies in a Modern Competitive Scenario: Understanding the Panorama for Security and Privacy Requirements

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