• DocumentCode
    2020581
  • Title

    Capturing parallel attacks within the data independence framework

  • Author

    Broadfoot, P.J. ; Roscoe, A.W.

  • Author_Institution
    Comput. Lab., Oxford Univ., UK
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    147
  • Lastpage
    159
  • Abstract
    We carry forward the work described in our previous papers (Broadfoot et al., 2000, Broadfoot and Roscoe, 2002, and Roscoe, 1998) on the application of data independence to the model checking of cryptographic protocols using CSP and FDR. In particular, we showed how techniques based on data independence could be used to justify, by means of a finite FDR check, systems where agents can perform an unbounded number of protocol runs. Whilst this allows for a more complete analysis, there was one significant incompleteness in the results we obtained: While each individual identity could perform an unlimited number of protocol runs sequentially, the degree of parallelism remained bounded. We report significant progress towards the solution of this problem, by "internalising" all or part of each agent identity within the "intruder" process. We consider the case where internal agents do introduce fresh values and address the issue of capturing the state of mind of internal agents (for the purposes of analysis).
  • Keywords
    communicating sequential processes; concurrency theory; cryptography; message authentication; protocols; CSP; FDR; cryptographic protocols; data independence framework; internalisation; intruder process; model checking; parallel attacks; protocol runs; Computer security; Conferences; Cryptographic protocols; Cryptography; Data security; Explosions; Laboratories; Parallel processing; Performance analysis; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Security Foundations Workshop, 2002. Proceedings. 15th IEEE
  • ISSN
    1063-6900
  • Print_ISBN
    0-7695-1689-0
  • Type

    conf

  • DOI
    10.1109/CSFW.2002.1021813
  • Filename
    1021813