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Cerberus: A Context-Aware Security Scheme for Smart Spaces presented by L.X.Hung u-Security Research Group 2005.10.10 The First IEEE International Conference on Pervasive Computing and Communications (PerCom’03)
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2 Agenda Security Requirement for Smart Space Cerberus Overview Security Service components Authentication Access Control Inference Engine Security Policy Related work and paper contribution Conclusion References
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3 Security Requirements for Smart Space Security itself has to be ‘ubiquitous’, non- intrusive, transparent Has to be multiple level Provide different levels of security depending on policies, context, and resources, Support security language that is: Descriptive, well-define, and flexible. Authentication Support authenticating human users, devices that enter and leaves smart room, applications
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4 GAIA Project A middleware infrastructure for ubiquitous applications Provides core services that make up smart space. Coordinates software entities and heterogeneous network devices Export services to query and utilize resources, Access and use current context, Provide framework to develop user-centric, resource-aware, context-sensitive, mobile applications.
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5 Cerberus overview 4 components Security service Context infrastructure Knowledge base (security policies) Inference engine
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6 Security Service components Identification: links an entity with id Authentication: to verify entity/principal (users, physical space, applications, mobile code) authentication strength vs. non-intrusiveness (smart badge) includes wearable devices, voice & face recognition, … Difference strength ~ confident values Need dynamic method to add new authentication devices Associate with access control policies and protocols
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7 Security Service components (cont’) Authentication (cont’) GPAM: Gaia Pluggable Authentication Modules extension of PAM GAMMs: Gaia Authentication Mechanism Module General authentication modules or protocols GADMs: Gaia Authentication Device Module Dependent on particular devices UIC based (Universally Interoperate Core): light- weight, high-performance, basic CORBA services
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8 Security Service components (cont’) Access Control To check whether principal P can perform a particular operation Forward inquiries from apps, service providers to Inference Engine Support Callback to app to inform possible context change that may trigger a change in access decision.
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9 Security Service components (cont’) Security Policies Written as rules Two kind of policies Used by authentication server At the time of login or authentication Determine confident level of authentication examples ConfidenceLevel (smart_watch, 70%) ConfidenceValue (P, V) :- ∃ device X (Authenticated(P,X) ∧ ConfidenceLevel (X, V) ) Access control policies Determine whether principal P is allowed access to a particular resource. eg. CanAccess (P, ColorPrinter ) :- ∃ number V (ConfidenceValue(P, V) ∧ V>60%)
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10 Security Service components (cont’) Inference Engine: 2 tasks 1 st Give a level of confidence when a user authenticate himself. Make use of authentication policies and context to assign confident level 2 nd Evaluate queries from apps whether a certain entity can access to particular resource. Make use of app-specific access control policies, credential of entities, contextual information
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11 Related work and Contribution Covington et al. [14, 15] Securing ‘Smart Home’ Extend RBAC to develop non-intrusive Access control mechanisms are integrated with a toolkit for gathering context information from sensors. Drawback: Language is based on logic, that is simplistic Cerberus: More expressive rule language (support binary operator, quantification, complex inferring) Address some issues in Stajano [16]
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12 Conclusion The dynamic, ubiquity and non-intrusiveness of Ubicomp present more challenges and raise issues Cerberus: Support multiple level authentications, context infrastructure captures rapidly changing context information and incorporates it into our knowledge base. Context-aware security policies are described in an expressive language and can be evaluated efficiently using an inference engine. Present a simple and efficient method for revoking access if context related information changes.
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13 References M. Román, C. K. Hess, R. Cerqueira, A. Ranganathan, R. H. Campbell, and K. Nahrstedt, "Gaia: A Middleware infrastructure to Enable Active Spaces," IEEE Pervasive Computing, 2002. V. Samar and R. Schemers, "Unified Login with Pluggable Authentication Modules (PAM)," RFC 86.0, 1995. M. Roman, F. Kon, and R. H. Campbell, "Reflective Middleware: From Your Desk to Your Hand," IEEE Distributed systems Online Journal, Special Issue on Reflective Middleware, 2001. J. Al-Muhtadi, D. Mickunas, and R. Campbell, "The Gaia Authentication Architecture," UIUC Technical Report (number pending) 2003.
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14 Thank you ! Questions & Discussion
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