Enhancing cooperativity in controlled query evaluation over ontologies

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Piero Bonatti , Gianluca Cima , Domenico Lembo , Francesco Magliocca , Lorenzo Marconi , Riccardo Rosati , Luigi Sauro , Domenico Fabio Savo
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引用次数: 0

Abstract

Controlled Query Evaluation (CQE) is a methodology designed to maintain confidentiality by either rejecting specific queries or adjusting responses to safeguard sensitive information. In this investigation, our focus centers on CQE within Description Logic ontologies, aiming to ensure that queries are answered truthfully as long as possible before resorting to deceptive responses, a cooperativity property which is called the “longest honeymoon”. Our work introduces new semantics for CQE, denoted as MC-CQE, which enjoys the longest honeymoon property and outperforms previous methodologies in terms of cooperativity.
We study the complexity of query answering in this new framework for ontologies expressed in the Description Logic DL-LiteR. Specifically, we establish data complexity results under different maximally cooperative semantics and for different classes of queries. Our results identify both tractable and intractable cases. In particular, we show that the evaluation of Boolean unions of conjunctive queries is the same under all the above semantics and its data complexity is in
. This result makes query answering amenable to SQL query rewriting. However, this favorable property does not extend to open queries, even with a restricted query language limited to conjunctions of atoms. While, in general, answering open queries in the MC-CQE framework is intractable, we identify a sub-family of semantics under which answering full conjunctive queries is tractable.
增强本体上受控查询计算的协同性
受控查询评估(CQE)是一种旨在通过拒绝特定查询或调整响应以保护敏感信息来维护机密性的方法。在本次调查中,我们的重点是描述逻辑本体中的CQE,旨在确保在诉诸欺骗性响应之前尽可能长时间地如实回答查询,这是一种被称为“最长蜜月”的协作特性。我们的工作为CQE引入了新的语义,表示为MC-CQE,它具有最长的蜜月属性,并且在协作性方面优于以前的方法。我们研究了用描述逻辑dl - l表达的本体在这个新框架下查询回答的复杂性。具体来说,我们建立了不同最大协作语义和不同查询类别下的数据复杂度结果。我们的结果确定了易处理和难以处理的病例。特别地,我们证明了在上述所有语义下,合取查询的布尔联合的求值是相同的,其数据复杂度为。这个结果使得查询应答能够适应SQL查询重写。但是,这个有利的特性不能扩展到打开查询,即使使用限于原子连词的受限查询语言也是如此。虽然一般来说,在MC-CQE框架中回答开放查询是棘手的,但我们确定了一个子语义族,在该语义族下回答完整的连接查询是可处理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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