Quantifiable integrity for Linked Data on the web

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Semantic Web Pub Date : 2023-07-18 DOI:10.3233/sw-233409
Christoph H.-J. Braun, Tobias Käfer
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Abstract

We present an approach to publish Linked Data on the Web with quantifiable integrity using Web technologies, and in which rational agents are incentivised to contribute to the integrity of the link network. To this end, we introduce self-verifying resource representations, that include Linked Data Signatures whose signature value is used as a suffix in the resource’s URI. Links among such representations, typically managed as web documents, contribute therefore to preserving the integrity of the resulting document graphs. To quantify how well a document’s integrity can be relied on, we introduce the notion of trust scores and present an interpretation based on hubs and authorities. In addition, we present how specific agent behaviour may be induced by the choice of trust score regarding their optimisation, e.g., in general but also using a heuristic strategy called Additional Reach Strategy (ARS). We discuss our approach in a three-fold evaluation: First, we evaluate the effect of different graph metrics as trust scores on induced agent behaviour and resulting evolution of the document graph. We show that trust scores based on hubs and authorities induce agent behaviour that contributes to integrity preservation in the document graph. Next, we evaluate different heuristics for agents to optimise trust scores when general optimisation strategies are not applicable. We show that ARS outperforms other potential optimisation strategies. Last, we evaluate the whole approach by examining the resilience of integrity preservation in a document graph when resources are deleted. To this end, we propose a simulation system based on the Watts–Strogatz model for simulating a social network. We show that our approach produces a document graph that can recover from such attacks or failures in the document graph.
网络上关联数据的可量化完整性
我们提出了一种使用Web技术在Web上发布具有可量化完整性的关联数据的方法,并在该方法中激励理性代理为链接网络的完整性做出贡献。为此,我们引入了自验证资源表示,其中包括链接数据签名,其签名值用作资源URI中的后缀。因此,这些表示之间的链接(通常作为web文档进行管理)有助于保持生成的文档图的完整性。为了量化文档的完整性可以依赖的程度,我们引入了信任分数的概念,并基于中心和权威给出了解释。此外,我们还介绍了如何通过选择优化的信任分数来诱导特定的代理行为,例如,一般情况下,但也使用一种称为额外到达策略(ARS)的启发式策略。我们以三方面的评估来讨论我们的方法:首先,我们评估了不同的图形度量作为信任分数对诱导代理行为和文档图的最终进化的影响。我们表明,基于中心和权威的信任分数诱导代理行为,有助于文档图中的完整性保存。接下来,我们评估了当一般优化策略不适用时,代理优化信任分数的不同启发式方法。我们表明,ARS优于其他潜在的优化策略。最后,我们通过检查资源被删除时文档图中完整性保存的弹性来评估整个方法。为此,我们提出了一个基于Watts-Strogatz模型的仿真系统来模拟社会网络。我们展示了我们的方法生成的文档图可以从文档图中的此类攻击或故障中恢复。
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来源期刊
Semantic Web
Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍: The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.
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