What is in your cookie box? Explaining ingredients of web cookies with knowledge graphs

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2023-08-21 DOI:10.3233/sw-233435

Geni Bushati, Sven Carsten Rasmusen, Anelia Kurteva, Anurag Vats, Petraq Nako, A. Fensel

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引用次数: 0

Abstract

The General Data Protection Regulation (GDPR) has imposed strict requirements for data sharing, one of which is informed consent. A common way to request consent online is via cookies. However, commonly, users accept online cookies being unaware of the meaning of the given consent and the following implications. Once consent is given, the cookie “disappears”, and one forgets that consent was given in the first place. Retrieving cookies and consent logs becomes challenging, as most information is stored in the specific Internet browser’s logs. To make users aware of the data sharing implied by cookie consent and to support transparency and traceability within systems, we present a knowledge graph (KG) based tool for personalised cookie consent information visualisation. The KG is based on the OntoCookie ontology, which models cookies in a machine-readable format and supports data interpretability across domains. Evaluation results confirm that the users’ comprehension of the data shared through cookies is vague and insufficient. Furthermore, our work has resulted in an increase of 47.5% in the users’ willingness to be cautious when viewing cookie banners before giving consent. These and other evaluation results confirm that our cookie data visualisation approach and tool help to increase users’ awareness of cookies and data sharing.

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你的饼干盒子里是什么?用知识图谱解释网络cookie的成分

通用数据保护条例(GDPR)对数据共享提出了严格的要求，其中之一是知情同意。一种常见的在线请求同意的方式是通过cookies。然而，通常情况下，用户接受在线cookie并不知道给定同意的含义和以下含义。一旦同意，饼干就会“消失”，人们就会忘记同意最初是被给予的。检索cookie和同意日志变得很有挑战性，因为大多数信息都存储在特定Internet浏览器的日志中。为了让用户意识到cookie同意所隐含的数据共享，并支持系统内的透明度和可追溯性，我们提出了一个基于知识图(KG)的工具，用于个性化cookie同意信息可视化。KG基于OntoCookie本体，该本体以机器可读的格式对cookie进行建模，并支持跨域的数据可解释性。评估结果证实，用户对通过cookie共享的数据的理解是模糊和不足的。此外，我们的工作导致用户在同意之前查看cookie横幅时谨慎的意愿增加了47.5%。这些和其他评估结果证实，我们的cookie数据可视化方法和工具有助于提高用户对cookie和数据共享的认识。

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

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

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.