Download presentation
Presentation is loading. Please wait.
1
Naftaly Minsky Rutgers University Law-Governed Interaction: a Decentralized Access-Control Mechanism
2
2 N. Minsky, Ottawa April/05 outline The challenges. The concept of law-governed interaction (LGI), and how it meets these challenges. An example: flexible regulation of dynamic coalitions. Conclusion: The release of LGI.
3
3 N. Minsky, Ottawa April/05 The Challenges Facing Access Control The distributed and open nature of systems, and their large scale. The need for more sophisticated policies, which may be statful (sensitive to the history of interaction), and proactive (not limited to permission/prohibition.) The need for communal (rather than server-centric) policies, such as: different servers subject to the same enterprise-wide policy P2P communities The need for interoperation between different policies, and for “conformance hierarchies” (e.g., in virtual enterprises) The real challenge is to meet all the above needs, via a single mechanism, and to do it scalably.
4
4 N. Minsky, Ottawa April/05 Server-Centric Access-Control (AC) Reference Monitor (RM) server It generally supports only stateless, purely reactive, ACL-based policies, enhanced with RBAC—and this is far from sufficient.
5
5 N. Minsky, Ottawa April/05 Enforcing a Communal AC Policy Enterprise-wide (communal) policy P Enterprise delegate The communal policy may be that certain type of transactions need to be monitores…
6
6 N. Minsky, Ottawa April/05 The Concept of Law-Governed Interaction (LGI) LGI is a message exchange mechanism that enables a community of distributed agents to interact under an explicit and strictly enforced policy, called the “law” of this community. Some characteristics of LGI: A communal, rather than server-centric, control. High expressive power, including stateful and proactive laws—which is sensitive to roles (in much more general manner than RBAC) Laws can be written either in prolog, or in Java Incremental deployment, and efficient execution A single system may have a multitude of interrelated laws, which may interoperate, and be hierarchically organized. Enforcement is decentralized---for scalability.
7
7 N. Minsky, Ottawa April/05 Centralized Enforcement of Communal Policies * The problems: potential congestion, and single point of failure m’ x u v y m ==> y m ==> x m Legend: P---Explicit statement of a policy. I---Policy interpreter S---the interaction state of the community P I S Reference monitor * Replication does not help, if S changes rapidly enough
8
8 N. Minsky, Ottawa April/05 Distributed Law-Enforcement under LGI L I S x u v y L I SxSx L I SvSv L I SySy L I SuSu m ==> y m’ m’’ m m ==> y m
9
9 N. Minsky, Ottawa April/05 The local nature of LGI laws Laws are defined locally, at each agent: They deal explicitly only with local events—such as the sending or arrival of a message. the ruling of a law for an event e at agent x is a function of e, and of the local control state CS X of x. a ruling can mandate only local operations at x. Local laws can have powerul global consequences— because of their global purview. This localization does not reduce the expressive power of LGI laws, and it provides scalability for many (althouh not all) laws.
10
10 N. Minsky, Ottawa April/05 Deployment of LGI (Using Distributed TCB) I I I I IIx y controller service adopt(L, name) adopt(…) m’ m’’ L m ==> y L
11
11 N. Minsky, Ottawa April/05 Motivating the Need for Interoperability, and for Policy-Hierarchy Consider a coalition C of enterprises {E 1,..., E n }, governed by a coalition-policy P C ---where each E i is governed by its own internal-policy P i. E3E3 E2E2 E1E1 P2P2 P1P1 P3P3 PCPC
12
12 N. Minsky, Ottawa April/05 The Main Problems The flexible formulation of these policies, so that (a) they will be consistent, and (b) their specification and evolution would be manageable. Enforcement of these policies in a scalable manner.
13
13 N. Minsky, Ottawa April/05 Example (cont.) E2E2 E3E3 E1E1 Roles: each Ei has its director Di; and the coalition C has a director D C. A director Di can mint Ei-currency $ i needed to pay for services provided by Ei and it can give D C some of this currency A director D C can distribute some of its B($ 1 ) budget among other directors A director D 2 can distribute its B($ 1 ) budget among agents at its enterprise B($ 1 ) B1B1 All service requests should be monitored PCPC P2P2 P1P1
14
14 N. Minsky, Ottawa April/05 Enforcement by Composition … Given the set {P C, P 1,..., P n } of policies. Construct a set {P i,j } of compositions: where P i,j = composition (P i, P C, P j ). Provide these compositions to the reference monitor (RM) that mediates all coalition-relevant interactions. Compositions were studied by: Gong & Qian 96, and by Bidan & Issarny 98,...
15
15 N. Minsky, Ottawa April/05 … and its Problematics It is unlikely for arbitrary, and independently formulated, policies to be consistent—such composition is likely to end with a big bang. Policy composition is computationally hard (McDaniel & Prakash 2002) and we need N^2 such compositions! Inflexibility: consider changing a single P i... Overly centralized, thus unscalable. The RM need to be trusted by all coalition members. Alternatively we can have N^2 different RMs, R i,j each trusted by {E i, C, E j }—still problematic.
16
16 N. Minsky, Ottawa April/05 The Proposed Approach Instead of creating N^2 compositions (P i, P C, P j ), we will enable each enterprise E i to create its own policy P i, subject only to the constraint that P i would conform to P C. We will then allow E i and E j to interoperate, once each of them enforces its own policy.
17
17 N. Minsky, Ottawa April/05 Hierarchy Organization of Coalition Policies PCPC P1P1 P2P2 PnPn superiorsubordinate P i is defined as subordinate to P c, as thus constrained to conform to it.
18
18 N. Minsky, Ottawa April/05 Interoperability Let us focus on the interoperability between E 2 and E 1 E3E3 E2E2 E1E1 P2P2 P1P1 P3P3 PCPC
19
19 N. Minsky, Ottawa April/05 Interoperability (cont.) imported(x,P 2,m) E2E2 E1E1 x y Authenticated by CA 2 and CA C Authenticated by CA 1 and CA C controller P1P1 P2P2 C x C y CS x II m export(m,y,P 1 )
20
20 N. Minsky, Ottawa April/05 Conclusion LGI implementation via the Moses middleware is to be released in May 2005, via: http://www.cs.rutgers.edu/moses/ http://www.cs.rutgers.edu/moses/ This release does not support policy hierarchy.
21
Questions?
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.