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Visualization of Automated Trust Negotiation
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  1. Visualization of Automated Trust Negotiation Danfeng Yao Michael Shin Brown University Goldman Sachs Inc. Roberto Tamassia William H. Winsborough Brown University University of Texas, San Antonio Supported in part by NSF grants CCF–0311510, IIS–0324846, CNS–0303577 and CNS-0325951

  2. Overview • Introduction to two-party automated trust negotiation (ATN) • Trust target graph (TTG) • Design of the visualization framework • Prototype implementation • Example of a visualization session • Demo of our visualization program

  3. Monitoring the release of sensitive credentials • Accessing protected resources requires releasing digital credentials • Credentials may be sensitive • Need to control the release of digital credentials • Trust Negotiation is an incremental, bilateral exchange of credentials and policies between resource owner and requester • Visualization of automated trust negotiation • Gives teaching and learning support for ATN users • Enables users to visually examine the ATN process • The combination of interactive visualization and ATN improves the security of protected resources • We demonstrate that Grappa and GraphViz (AT&T) are suitable graph drawing systems for visualizing ATN

  4. Request UID RequestBBB SendBBB Send UID Grant the discount A simple trust negotiation example Alice Request for discount

  5. Primary trust target Request credential Sensitive, requestproof Sensitive, request more credential Send proof Send credential Grant the resource A general trust negotiation Protocol Request for resource Alice

  6. Trust target graph • Trust target graph (TTG) is a directed graph representing the state of negotiation [Winsborough Li ’02] • The negotiation succeeds when the primary trust target is satisfied • Fails when the primary target cannot be satisfied, or when neither negotiator changes the graph • TTG can have cycles and be non-planar • Construction of TTG • Each negotiator keeps a local copy of TTG • Nodes are trust targets: • < Amazon: Amazon.discount ?Alice > • The state of a node: unknown, satisified, or unsatisfied • Edges represent implication and control relationships • Satisfied states propagate along the edges • Negotiators take turns extending the TTG by adding new edges and nodes to the current graph • At the beginning TTG contains only the primary trust target • The new TTG is a supergraph of the previous one • Associated credentials or policies are transmitted

  7. Amazon: Univ.Student ? Alice Alice: BBB.member ? Amazon Alice: BBB.member ? Amazon Amazon: Univ.Student ? Alice Alice: Amazon ? Amazon Amazon: Amazon.discount ? Alice TTG construction of the example Amazon: Amazon.discount ? Alice

  8. Components of our ATN visualization framework

  9. Prototype implementation • The visualizer displays the construction of TTG for negotiators • Uses Grappa system [Barghouti, Mocenigo, Lee. GD ‘97], a Java port of GraphViz system [Ellson, Gansner, Koutsofios, North, Woodhull et al] for graph drawing • Layout provided by dot in GraphViz • The upward drawing heuristics and hierarchical (layered) drawing features are suitable for drawing directed graphs such as TTGs • Layout algorithms try to avoid edge crossings and reduce edge length • Colors and shapes of nodes and edges represent different types in TTG and can be customized • Displays local credentials, remote credentials, and policies

  10. Intersection target Linked role target Standard target Trivial target

  11. Edge types

  12. Demo of a visualization session • Requester: Alice • Works at purchase department in Medix Fund (MedixFund.purchasingA) • She considers this credential sensitive • Resource owner: Medical Supply Company (MedSup) • A member of ReliefNet (ReliefNet.member) • Requested resource: Discount from MedSup • MedSup.discount • Delegation credentials transfer privileges between roles • Role provisioner at ReliefNet is delegated to MedixFund.purchasingA • cPartner at Medix Fund is delegated to ReliefNet.member • Discount is given toprovisioner at ReliefNet

  13. ATN-Vis Demo

  14. Example -- Start Requester: Alice Provider: Medical Supply (MedSup)

  15. Example -- 3% progress

  16. Example -- 16% progress

  17. Example -- 19% progress

  18. Example -- 23% progress

  19. Example -- 29% progress

  20. Example -- 42% progress

  21. Example -- 45% progress

  22. Example -- 52% progress

  23. Example -- 61% progress

  24. Example -- 71% progress

  25. Example -- 77% progress

  26. Example -- 74% progress

  27. Example -- 84% progress

  28. Example -- 97% progress

  29. Example -- 100% progress

  30. Related Work • Graph drawing systems • Grappa [Barghouti, Mocenigo, Lee. GD ‘97] • GraphViz [Ellson, Gansner, Koutsofios, North, Woodhull et al] • Visualization of protocols • [Hall, Moore, Pratt, Leslie. SIGCOMM Workshop ‘03] • [Zhao, Mayo. ICEE ’02] • [Koch, Parisi-Presicce. FASE ‘03] • Trust negotiation • [Winsborough, Seamons, Jones. DISCEX’00] • [Yu, Ma, Winslett. CCS’00] • [Winsborough, Li. POLICY ’02] • [Li, Du, Boneh ‘03] • Combination of visualization and automated protocols • Anomaly detection [Teoh, Zhang, Tseng, Ma, Wu. VizSEC/DMSEC ‘04] • Mining geo-spatial datasets [Keim, Panse, Sips, North. CG ‘04]

  31. Conclusions and future work • We have described the architecture and data model of an interactive visualization framework for ATN • We have presented a prototype of our ATN visualization framework • Grappa and GraphViz are suitable tools for drawing trust target graphs in ATN • For future work, we plan to bring more interactive components into the implementation • Provide more interactive explanations of texts inside TTG nodes • Visualization and modification of negotiation strategies