• DocumentCode
    3006711
  • Title

    Decentralized Trust Driven Access Control for Mobile Content Sharing

  • Author

    Vidyalakshmi, B.S. ; Wong, Raymond K. ; Chi-Hung Chi

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    June 27 2013-July 2 2013
  • Firstpage
    239
  • Lastpage
    246
  • Abstract
    Varieties and volume of content generated from mobile devices contribute to the complications on research and analysis on big data. Increases in content generation through mobile devices, increasing penetration, and decentralized nature are the leading reasons of Peer-to-Peer (P2P) content sharing among mobile devices. With technologies like Bluetooth and NFC paving way for easier and less expensive ad hoc data transfer, content sharing among smartphones is realistic and achievable. Traditional access control among peers in a P2P network assumes that all data is shared among all peers. However, this may not always be the case as data on the smartphones can be personal or confidential. There is a need to address sharing specific data with specific peer, based on peer´s trustworthiness with the host peer. We propose a model which controls access to files at a category level rather than at file or user level. We argue that the model preserves peers´ autonomy while preserving P2P decentralized structure.
  • Keywords
    computer network security; mobile computing; peer-to-peer computing; smart phones; trusted computing; Bluetooth; P2P content sharing; P2P decentralized structure; ad hoc data transfer; content generation; decentralized trust driven access control; file access; host peer; mobile content sharing; mobile devices; peer trustworthiness; peer-to-peer content; smartphones; Access control; Computational modeling; Context; Mobile communication; Peer-to-peer computing; Smart phones;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2013 IEEE International Congress on
  • Conference_Location
    Santa Clara, CA
  • Print_ISBN
    978-0-7695-5006-0
  • Type

    conf

  • DOI
    10.1109/BigData.Congress.2013.40
  • Filename
    6597143