Towards Controlled Query Evaluation for Incomplete First-Order Databases

Biskup, Joachim; Tadros, Cornelia; Wiese, Lena

doi:10.1007/978-3-642-11829-6_16

Cited by 16 publications

(11 citation statements)

References 18 publications

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“…In the literature of controlled query evaluation [Biskup 2011;Biskup and Weibert 2008;Biskup et al 2010Biskup and Tadros 2012], a secret is preserved if for any sequence of queries there are two different models that are indistinguishable in the sense that they produce the same answers to the queries; one being a model of the secret and the other a model of the negation of the secret. Our framework also respects this property of secrecy-preservation.…”

Section: Remark Regarding the Relationship Between Cqe And Our Msq Symentioning

confidence: 99%

A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases

Jia

Slutzki

Honavar

2014

ACM Trans. Comput. Logic

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In many applications, Knowledge Bases (KBs) contain confidential or private information (secrets). The KB should be able to use this secret information in its reasoning process but in answering user queries care must be exercised so that secrets are not revealed to unauthorized users. We consider this problem under the Open World Assumption (OWA) in a setting with multiple querying agents M 1 , . . . , M m that can pose queries against the KB K and selectively share answers that they receive from K with one or more other querying agents. We assume that for each M i , the KB has a prespecified set of secrets S i that need to be protected from M i . Communication between querying agents is modeled by a communication graph, a directed graph with self-loops. We introduce a general framework and propose an approach to secrecy-preserving query answering based on sound and complete proof systems. The idea is to hide the truthful answer from a querying agent M i by feigning ignorance without lying (i.e., to provide the answer 'Unknown' to a query q if it needs to be protected. Under the OWA, a querying agent cannot distinguish between the case that q is being protected (for reasons of secrecy) and the case that it cannot be inferred from K. In the pre-query stage we compute a set of envelopes E 1 , . . . , E m (restricted to a finite subset of the set of formulae that are entailed by K) so that S i ⊆ E i , and a query α posed by agent M i can be answered truthfully whenever α / ∈ E i and ¬α / ∈ E i . After the pre-query stage, the envelope is updated as needed. We illustrate this approach with two simple cases: the Propositional Horn KBs and the Description Logic AL KBs. ACM Reference Format:Jia Tao, Giora Slutzki, and Vasant Honavar. 2014. A conceptual framework for secrecy-preserving reasoning in knowledge bases.

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Section: Remark Regarding the Relationship Between Cqe And Our Msq Symentioning

confidence: 99%

A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases

Jia

Slutzki

Honavar

2014

ACM Trans. Comput. Logic

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“…u ∈ n ix i ∩ S(Vs) u = null ∨ ¬ϕ). 8 For distinction from the notion of relevant attribute/variable used in Sections II-A and II-B.…”

Section: Secrecy Instancesmentioning

confidence: 99%

“…If that is the case, the answer is distorted by either lying or refusal or combined lying and refusal. In [8], they extend CQE to restricted incomplete FO logic databases via a transformation into a propositional language. This approach seem to be incomparable to ours.…”

Section: Related Workmentioning

confidence: 99%

Achieving Data Privacy through Secrecy Views and Null-Based Virtual Updates

Bertossi

2013

IEEE Trans. Knowl. Data Eng.

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We may want to keep sensitive information in a relational database hidden from a user or group thereof. We characterize sensitive data as the extensions of secrecy views. The database, before returning the answers to a query posed by a restricted user, is updated to make the secrecy views empty or a single tuple with null values. Then, a query about any of those views returns no meaningful information. Since the database is not supposed to be physically changed for this purpose, the updates are only virtual, and also minimal. Minimality makes sure that query answers, while being privacy preserving, are also maximally informative. The virtual updates are based on null values as used in the SQL standard. We provide the semantics of secrecy views, virtual updates, and secret answers to queries. The different instances resulting from the virtually updates are specified as the models of a logic program with stable model semantics, which becomes the basis for computation of the secret answers.Index Terms-Data privacy, views, query answering, null values, view updates, answer set programs, database repairs.

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“…Preserving secrecy in a database setting is a problem of paramount importance and it has been studied for a long time, see Biskup and Weibert (2008); Biskup et al (2010);Sicherman et al (1983). With the advent of the semantic web and its increasingly pervasive usage, there is a lot of interest in studying this problem in knowledge base (KB) setting, see Bao et al (2007); Grau et al (2013); Tao et al (2010Tao et al ( , 2014.…”

Section: Secrecy-preserving Query Answering Problemmentioning

confidence: 99%

“…One approach to secrecy in incomplete database was presented in Biskup and Weibert (2008); Biskup et al (2010); Biskup and Tadros (2012) in the form of controlled query evaluation (CQE). The idea behind CQE is that rather than providing strict access control to data, the CQE approach enforces secrecy by checking (at run time) whether from a truthful answer to a query a user can deduce secret information.…”

Section: Secrecy-preserving Query Answering Problemmentioning

confidence: 99%

Secrecy-preserving reasoning in simple description logic knowledge bases

Sivaprakasam

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Towards Controlled Query Evaluation for Incomplete First-Order Databases

Cited by 16 publications

References 18 publications

A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases

A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases

Achieving Data Privacy through Secrecy Views and Null-Based Virtual Updates

Secrecy-preserving reasoning in simple description logic knowledge bases

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