Mixing Description Logics in Privacy-Preserving Ontology Publishing

Baader, Franz; Nuradiansyah, Adrian

doi:10.1007/978-3-030-30179-8_7

Cited by 1 publication

(5 citation statements)

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“…It is currently not clear whether and how our results can be extended from singleton policies to general ones consisting of a finite set of EL concepts. The papers [2,6] investigate both compliance and safety for such general policies, but they restrict the data to EL instance stores. The work in [4] considers general quantified ABoxes and policies, but presents results for compliance only.…”

Section: Discussionmentioning

confidence: 99%

“…First, instead of making the data public, one can provide only restricted access through queries, whose answers are monitored by a "censor", which may decide not to give an answer or even lie if needed to satisfy the constraints [7][8][9]. Second, one can publish the data in an appropriately anonymized form, while keeping as much information about individuals as is allowed by the policy available [2,4,6,10,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…The works in this area differ from each other in several aspects. The papers [2,4,6] and this one allow for arbitrary modifications of the original data set, as long as the new data is logically implied by the original one. In contrast, the work from [10,13,14] restricts modifications to the application of certain anonymization operations.…”

Section: Introductionmentioning

confidence: 99%

“…While in the work described in [10,13,14] RDF graphs are used to represent the data and conjunctive queries to describe the policy, the papers [2,4,6] consider the setting where DL ABoxes represent the data and concepts of the DL EL describe the policy. More precisely, a restricted form of ABoxes, called instance store, is considered in [2,6], whereas in [4] and in the present paper so-called quantified ABoxes are employed. Basically, quantified ABoxes extend traditional DL ABoxes by allowing for anonymized individuals, which from a logical point of view are represented as existentially quantified variables.…”

Section: Introductionmentioning

confidence: 99%

“…Here, we employ the same formal setup as [4] but addresses safety. The only work where the formalisms for representing the attacker's knowledge and formalizing the data differ is [6].…”

Section: Introductionmentioning

confidence: 99%

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Safety of quantified ABoxes w.r.t. singleton ε L policies

Baader

Kriegel

Nuradiansyah

et al. 2021

Proceedings of the 36th Annual ACM Symposium on Applied Computing

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In recent work, we have shown how to compute compliant anonymizations of quantified ABoxes w.r.t. EL policies. In this setting, quantified ABoxes can be used to publish information about individuals, some of which are anonymized. The policy is given by concepts of the Description Logic (DL) EL, and compliance means that one cannot derive from the ABox that some non-anonymized individual is an instance of a policy concept. If one assumes that a possible attacker could have additional knowledge about some of the involved non-anonymized individuals, then compliance with a policy is not sufficient. One wants to ensure that the quantified ABox is safe in the sense that none of the secret instance information is revealed, even if the attacker has additional compliant knowledge. In the present paper, we show that safety can be decided in polynomial time, and that the unique optimal safe anonymization of a non-safe quantified ABox can be computed in exponential time, provided that the policy consists of a single EL concept.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Here, we employ the same formal setup as [4] but addresses safety. The only work where the formalisms for representing the attacker's knowledge and formalizing the data differ is [6].…”

Section: Introductionmentioning

confidence: 99%

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