Enabling Privacy Preserving Data Analytics
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Beschreibung
This book highlights the importance of digital privacy as an allied and supporting field to cybersecurity. The authors aim to underscore the fact that digital privacy is important sub-field of cybersecurity and must be differentiated from the social science and digital humanities view of privacy.
This book discusses digital privacy from various viewpoints in relation to cyber-security. The authors begin with Chapter 1, by emphasizing the fact that digital privacy must be viewed and addressed as a collective (and not an individual) problem. Therefore, solutions designed must include several perspectives ranging from decision making algorithms that assess the cost-benefit ratio for all parties involved in the digital operation. In Chapters 2, 3, 4 and 5, the authors discuss the implications from the adversarial and benign perspectives, of transforming data to ensure privacy. The authors also discuss performance, and some solutions to help alleviate this especially in scenarios involving large data and/or low powered/processing systems. In Chapters 6 and 7, the authors discuss the benefits of supporting user decision making and preventing privacy breaches that arise from inadvertent disclosures of sensitive personal information. Chapter 8 discusses possible avenues for future work centred around aspects, such as data transformation to support privacy preserving machine learning, privacy decision making and disclosure risks.
This book targets researchers working in digital privacy and cybersecurity as well as advanced-level students studying this field. Policy makers in governments and organizations will also find this book to be a valuable resource.
This book highlights the importance of digital privacy as an allied and supporting field to cybersecurity. The authors aim to underscore the fact that digital privacy is important sub-field of cybersecurity and must be differentiated from the social science and digital humanities view of privacy.
This book discusses digital privacy from various viewpoints in relation to cyber-security. The authors begin with Chapter 1, by emphasizing the fact that digital privacy must be viewed and addressed as a collective (and not an individual) problem. Therefore, solutions designed must include several perspectives ranging from decision making algorithms that assess the cost-benefit ratio for all parties involved in the digital operation. In Chapters 2, 3, 4 and 5, the authors discuss the implications from the adversarial and benign perspectives, of transforming data to ensure privacy. The authors also discuss performance, and some solutions to help alleviate this especially in scenarios involving large data and/or low powered/processing systems. In Chapters 6 and 7, the authors discuss the benefits of supporting user decision making and preventing privacy breaches that arise from inadvertent disclosures of sensitive personal information. Chapter 8 discusses possible avenues for future work centred around aspects, such as data transformation to support privacy preserving machine learning, privacy decision making and disclosure risks.
This book targets researchers working in digital privacy and cybersecurity as well as advanced-level students studying this field. Policy makers in governments and organizations will also find this book to be a valuable resource.
Distinguishes the field of Digital Privacy from Digital (cyber) security Highlights the interdependencies between good digital privacy and security assurances Covers domains such as attacks to data pseudonymisation and anonymisation schemes
Autor*in
Anne V. D. M. Kayem
Themen in »Enabling Privacy Preserving Data Analytics«
Privacy Enhancing Technologies Digital Privacy Privacy Threats Privacy Attacks Data Anonymisation Data Pseudonymisation Privacy Preserving Machine Learning Privacy Setting Recommendations Data Profiling Privacy Preferences