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On preserving privacy in content-oriented networks

Published: 19 August 2011 Publication History
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  • Abstract

    The recent literature has hailed the benefits of content-oriented network architectures. However, such designs pose a threat to privacy by revealing a user's content requests. In this paper, we study how to ameliorate privacy in such designs. We present an approach that does not require any special infrastructure or shared secrets between the publishers and consumers of content. In lieu of any informational asymmetry, the approach leverages computational asymmetry by forcing the adversary to perform sizable computations to reconstruct each request. This approach does not provide ideal privacy, but makes it hard for an adversary to effectively monitor the content requests of a large number of users.

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    1. On preserving privacy in content-oriented networks

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      cover image ACM Conferences
      ICN '11: Proceedings of the ACM SIGCOMM workshop on Information-centric networking
      August 2011
      80 pages
      ISBN:9781450308014
      DOI:10.1145/2018584
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 19 August 2011

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      Author Tags

      1. content-oriented networking
      2. privacy

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      • Research-article

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      SIGCOMM '11
      Sponsor:
      SIGCOMM '11: ACM SIGCOMM 2011 Conference
      August 19, 2011
      Ontario, Toronto, Canada

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      ICN '11 Paper Acceptance Rate 12 of 50 submissions, 24%;
      Overall Acceptance Rate 133 of 482 submissions, 28%

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      • (2023)Security Overall in Information‐Centric NetworksAttribute‐based Encryption (ABE)10.1002/9781119989387.ch12(195-214)Online publication date: 6-Oct-2023
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