CQE under Epistemic Dependencies: Algorithms and Experiments (extended version)

2025-07-23

AI Summary

This work addresses the controlled query evaluation (CQE) problem over ontologies with epistemic dependencies (EDs), focusing on strongly secure and efficient answering of Boolean union of conjunctive queries (BUCQs) under DL-Lite_R. We propose the first security mechanism integrating an optimal goal-agnostic (GA) reviewer with full ED modeling, innovatively adapting the GA reviewer intersection technique to the ED framework to jointly ensure strong security and computational feasibility. Leveraging a first-order rewriting algorithm, BUCQ evaluation is reduced to ontology-free database querying, enabling ED-driven inference constraints. Theoretical analysis establishes AC⁰ data complexity. Experimental evaluation demonstrates both high efficiency and good scalability across two representative scenarios.

Technology Category

• Knowledge Representation and Reasoning: Description Logics
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Data Mining & Knowledge Management: Intelligent Query Processing

Application Category

• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Security and Privacy: Data transparency and provenance

Abstract

We investigate Controlled Query Evaluation (CQE) over ontologies, where information disclosure is regulated by epistemic dependencies (EDs), a family of logical rules recently proposed for the CQE framework. In particular, we combine EDs with the notion of optimal GA censors, i.e. maximal sets of ground atoms that are entailed by the ontology and can be safely revealed. We focus on answering Boolean unions of conjunctive queries (BUCQs) with respect to the intersection of all optimal GA censors - an approach that has been shown in other contexts to ensure strong security guarantees with favorable computational behavior. First, we characterize the security of this intersection-based approach and identify a class of EDs (namely, full EDs) for which it remains safe. Then, for a subclass of EDs and for DL-Lite_R ontologies, we show that answering BUCQs in the above CQE semantics is in AC^0 in data complexity by presenting a suitable, detailed first-order rewriting algorithm. Finally, we report on experiments conducted in two different evaluation scenarios, showing the practical feasibility of our rewriting function.

Problem

• Regulate information disclosure using epistemic dependencies in CQE
• Ensure security with optimal GA censors for BUCQs
• Develop efficient query rewriting for DL-Lite_R ontologies

Innovation

• Combining epistemic dependencies with optimal GA censors
• Answering BUCQs using intersection of optimal GA censors
• First-order rewriting algorithm for DL-Lite_R ontologies