Optimality and complexity of inference-proof data filtering and CQE

Abstract

The ample literature on confidentiality-preserving data publishing - and controlled query evaluation (CQE) in particular - leaves several questions open. Are the greedy data-filtering algorithms adopted in the literature maximally cooperative? Can novel secure view formats or answer distortion methods improve security or cooperativeness? What is the inherent complexity of confidentiality-preserving data publishing under different constraints, such as cooperativeness and availability? Can the theoretical results on CQE be systematically extended to more general settings? In this paper we answer the above questions using a completely generic, abstract data filtering framework, independent from any syntactic details and data source encodings, and compatible with all possible distortion methods. Some of the main results are: Refusal-based filterings can be adopted as a normal form for all kinds of filterings; greedy refusal-based filterings are optimal; cooperativeness checks and some availability checks are coNP-hard in the simplest case. © 2014 Springer International Publishing Switzerland.