Large-scale Web security systems usually involve cooperation between domains with non-identical policies. The network management and Web communication software used by the different organizations presents a stumbling block. Many of the tools used by the various divisions do not have the ability to communicate network management data with each other. At best, this means that manual human intervention into the communication protocols used at various network routers and endpoints is required. Developing practical, sound, and automated ways to compose policies to bridge these differences is a long-standing problem. One of the key subtleties is the need to deal with inconsistencies and defaults where one organization proposes a rule on a particular feature, and another has a different rule or expresses no rule. A general approach is to assign priorities to rules and observe the rules with the highest priorities when there are conflicts.
The present methods have inherent inefficiency, which heavily restrict their practical applications. A new, efficient algorithm combines policies utilized for Web services. The method is based on an algorithm that allows an automatic and scalable composition of security policies between multiple organizations. It is based on defeasible policy composition, a promising approach for finding conflicts and resolving priorities between rules.
In the general case, policy negotiation is an intractable problem. A promising method, suggested in the literature, is when policies are represented in defeasible logic, and composition is based on rules for non-monotonic inference. In this system, policy writers construct metapolicies describing both the policy that they wish to enforce and annotations describing their composition preferences. These annotations can indicate whether certain policy assertions are required by the policy writer or, if not, under what circumstances the policy writer is willing to compromise and allow other assertions to take precedence. Meta-policies are specified in defeasible logic, a computationally efficient non-monotonic logic developed to model human reasoning.
One drawback of this method is that at one point the algorithm starts an exhaustive search of all subsets of the set of conclusions of a defeasible theory. Although the propositional defeasible logic has linear complexity, the set of conclusions here may be large, especially in real-life practical cases. This phenomenon leads to an inefficient exponential explosion of complexity.
The current process of getting a Web security policy from combination of two meta-policies consists of two steps. The first is generating a new meta-policy that is a composition of the input meta-policies, and the second is mapping the meta-policy onto a security policy. The new algorithm avoids the exhaustive search in the current algorithm, and provides a security policy that matches all requirements of the involved meta-policies.
This work was done by Farrokh Vatan and Joseph G. Harman of Caltech for NASA’s Jet Propulsion Laboratory. For more information, download the Technical Support Package (free white paper) at www.techbriefs.com/tsp under the Information Sciences category.
The software used in this innovation is available for commercial licensing. Please contact Daniel Broderick of the California Institute of Technology at
This Brief includes a Technical Support Package (TSP).
Efficient Web Services Policy Combination
(reference NPO-47279) is currently available for download from the TSP library.
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Overview
The document presents a new efficient algorithm for combining security policies utilized in web services, developed by researchers at the Jet Propulsion Laboratory (JPL) and the University of Michigan. The primary goal of this research is to automate and streamline the negotiation of network communication protocols among various military services, addressing the challenges posed by incompatible tools and manual interventions that are often tedious and error-prone.
The proposed algorithm is based on defeasible logic, which allows for the representation of policies as meta-policies. Each meta-policy consists of a pair of components: P_req, which defines strict requirements, and P_reas, which outlines the reasoning behind these requirements, including annotations for composition preferences. This structure enables policy writers to specify not only the necessary assertions but also the conditions under which they are willing to compromise.
The document highlights the limitations of previous algorithms, particularly one referenced in the literature, which suffers from inefficiencies due to exhaustive searches through large sets of conclusions derived from policies. The new algorithm overcomes this inefficiency by employing a linear search through the elements of the policy conclusions, resulting in an overall quadratic time complexity relative to the size of the initial policies. This improvement is significant for real-world applications where the size of policy sets can be substantial.
Additionally, the paper provides an overview of defeasible logic, which encompasses various types of knowledge, including facts, strict rules, defeasible rules, defeaters, and superiority relations. This framework allows for nuanced reasoning about policies, accommodating exceptions and conflicting rules.
The document emphasizes the importance of having a simple, intuitive, and formally grounded methodology for policy negotiation that can be efficiently implemented on existing programming platforms. It also discusses the potential for this research to enhance automated network management and improve communication protocols within military contexts.
In summary, the research offers a promising approach to policy negotiation that not only addresses the complexities of combining security policies but also aims to facilitate better communication and interoperability among diverse systems, ultimately contributing to more reliable and efficient network management solutions.
