In ownership-based access control frameworks with the possibility of delegating permissions and administrative rights, chains of delegated accesses will form. There are different ways to treat these delegation chains when revoking rights, which give rise to different revocation schemes. Hagström et al. [8] proposed a framework for classifying revocation schemes, in which the different revocation schemes are defined graph-theoretically; they motivate the revocation schemes in this framework by presenting various scenarios in which the agents have different reasons for revocating. This paper is based on the observation that there are some problems with Hagström et al.'s definitions of the revocation schemes, which have led us to propose a refined framework with new graph-theoretic definitions of the revocation schemes. In order to formally study the merits and demerits of various definitions of revocation schemes, we propose to apply the axiomatic method originating in social choice theory to revocation schemes. For formulating an axiom, i.e. a desirable property of revocation frameworks, we propose a logic, Trust Delegation Logic (TDL), with which one can formalize the different reasons an agent may have for performing a revocation. We show that our refined graph-theoretic definitions of the revocation schemes, unlike Hagström et al.'s original definitions, satisfy the desirable property that can be formulated using TDL.

Abstract-In ownership-based access control frameworks with the possibility of delegating permissions and administrative rights, chains of delegated accesses will form. There are different ways to treat these delegation chains when revoking rights, which give rise to different revocation schemes. One possibility studied in the literature is to revoke rights by issuing negative authorizations, meant to ensure that the revocation is resilient to a later reissuing of the rights, and to resolve conflicts between principals by giving precedence to predecessors, i.e. principals that come earlier in the delegation chain. However, the effects of negative authorizations have been defined differently by different authors. Having identified three definitions of this effect from the literature, the first contribution of this paper is to point out that two of these three definitions pose a security threat. However, avoiding this security threat comes at a price: We prove that with the safe definition of the effect of negative authorizations, deciding whether a principal does have access to a resource is an NP-complete decision problem. We discuss two limitations that can be imposed on an access-control system in order to reduce the complexity of the problem back to a polynomial complexity: Limiting the length of delegation chains to an integer m reduces the runtime complexity of determining access to O(n m ), and requiring that principals form a hierarchy that graph-theoretically forms a rooted tree makes this decision problem solvable in quadratic runtime. Finally we discuss an approach that can mitigate the complexity problem in practice without fully getting rid of NP-completeness.

The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

On 19 September 2022, the first workshop on AI for Manufacturing (AI4M Workshop) took place at ECML-PKDD, the European Conference on Machine Learning and Principles and Practice for Knowledge Discovery in Databases. The workshop brought together researchers and practitioners, from academia and industry, contributing their perspectives. This special section includes five articles in which Artificial Intelligence methods are used to address real problems in the manufacturing industry, ranging from the supply chain, to production, to quality insurance, and predictive maintenance. In this introduction, we present a high-level overview of the current state of the area: observed trends and the main open challenges. This overview is based on these papers, the keynote presentation, the panel discussion, and the discussion that emerged during the workshop.