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Securecsocial: Secure Cloud-based Social Network

Securecsocial: Secure Cloud-based Social Network

Securecsocial: Secure Cloud-based Social Network
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Securecsocial: Secure Cloud-based Social Network Hardback - 2019

by Pradeep Atrey

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Details

  • Title Securecsocial: Secure Cloud-based Social Network
  • Author Pradeep Atrey
  • Binding Hardback
  • Condition New
  • Pages 160
  • Volumes 1
  • Language ENG
  • Publisher World Scientific Publishing Company
  • Publication date 2019-08-30
  • Features Bibliography, Index
  • Bookseller's Inventory # 35881209-n
  • ISBN 9789811205910 / 9811205914
  • Weight 0.85 lbs (0.39 kg)
  • Dimensions 9 x 6 x 0.44 in (22.86 x 15.24 x 1.12 cm)
  • Category Computer - Internet
  • Library of Congress subjects Computer networks - Security measures, Computer network architectures
  • Library of Congress Catalogue Number 2019018483
  • Dewey Decimal Code 384.38
  • Quantity available 5

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Reader reviews for Securecsocial: Secure Cloud-based Social Network

From the publisher

The use of online social networks (OSNs) has grown exponentially in recent years, and these OSNs continue to have an ever-increasing impact on human lives. There are many concerns regarding the privacy of users in these environments, such as how trustworthy the social network operators (SNOs) are.

This book presents a way to tackle the security and privacy issues in current OSNs through a new framework for online social networking, based on distributed cloud-based datacenters (CDCs) and using Shamir's secret sharing (SSS) as the method of encrypting user profile data. The framework aims to fulfill two contradictory goals: maintaining the utility of an OSN and preserving privacy of its users. The key feature of the framework lies in relinquishing control of a central authority over user's data (which is what usually happens in the current OSNs, e.g. Facebook keeps all our data) and distributing it to multiple CDCs in encrypted form. The use of SSS ensures perfect security, which means that the security of data does not rely on any unproven computational assumptions.

In this unique book, SNOs are considered as an adversary instead of external adversary. This paves the way for researchers to think beyond the privacy setting mechanism within an OSN to protect users' data.

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