• Contact

  • Newsletter

  • About us

  • Delivery options

  • Prospero Book Market Podcast

  • Enabling Privacy Preserving Data Analytics

    Enabling Privacy Preserving Data Analytics by Kayem, Anne V. D. M.;

    Series: Advances in Information Security; 92;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 213.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        88 752 Ft (84 526 Ft + 5% VAT)
      • Discount 20% (cc. 17 750 Ft off)
      • Discounted price 71 002 Ft (67 621 Ft + 5% VAT)

    88 752 Ft

    db

    Availability

    Not yet published.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Long description:

    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.

    More

    Table of Contents:

    Part I Overview.- Chapter 1 Introduction.- Part II Data De-Anonymisation.- Chapter 2 De-Anonymisation Mechanisms - An Overview.- Part III Anonymisation Approaches,- Chapter 3 Multi-Objective Anonymisation.- Chapter 4 High-Dimensional Data - Privacy Considerations.- Chapter 5 Accounting for User Privacy Preferences.- Part IV Usable Privacy - A Discussion.- Chapter 6 Privacy Recommender Systems.- Chapter 7 Identifying Personal Information in Textual Data.- Part V Conclusions and Future Work.- Chapter 8 Conclusions.- Appendix 1.- Appendix 2.- Glossary.- Index.

    More