Comparison of De-Identification Techniques for Privacy Preserving Data Analysis in Vehicular Data Sharing

Löbner, Sascha; Tronnier, Frédéric; Pape, Sebastian; Rannenberg, Kai

doi:10.1145/3488904.3493380

Cited by 11 publications

(7 citation statements)

References 25 publications

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“…It has also been shown that if users are aware that a tool should protect their privacy, they are getting biased and tend toward being more concerned about potential privacy issues of the tool than for non-privacy tools [4,5]. Further problems of integrating PETs into existing services are that, on the one hand, it is hard to decide which of the many PETs is the best choice [43,62] and that, on the other hand, it is hardly possible to ask the users about their preferences since in most cases the users do not notice the main achievement of the PET to protect their privacy, but rather things such as increased latency, more complex processes, or similar side effects.…”

Section: Discussionmentioning

confidence: 99%

Acceptance Factors of Privacy-Enhancing Technologies on the Basis of Tor and JonDonym

Pape

Harborth

2023

Human Factors in Privacy Research

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This chapter provides information about acceptance factors of privacy-enhancing technologies (PETs) based on our research why users are using Tor and JonDonym, respectively. For that purpose, we surveyed 124 Tor users (Harborth and Pape 2020) and 142 JonDonym users (Harborth Pape 2020) and did a quantitative evaluation (PLS-SEM) on different user acceptance factors. We investigated trust in the PET and perceived anonymity (Harborth et al. 2021; Harborth et al. 2020; Harborth and Pape 2018), privacy concerns, and risk and trust beliefs (Harborth and Pape 2019) based on Internet Users Information Privacy Concerns (IUIPC) and privacy literacy (Harborth and Pape 2020). The result was that trust in the PET seems to be the major driver. Furthermore, we investigated the users’ willingness to pay or donate for/to the service (Harborth et al. 2019). In this case, risk propensity and the frequency of perceived improper invasions of users’ privacy were relevant factors besides trust in the PET. While these results were new in terms of the application of acceptance factors to PETs, none of the identified factors was surprising. To identify new factors and learn about differences in users’ perceptions between the two PETs, we also did a qualitative analysis of the questions if users have any concerns about using the PET, when they would be willing to pay or donate, which features they would like to have and why they would (not) recommend the PET (Harborth et al. 2021; Harborth et al. 2020). To also investigate the perspective of companies, we additionally interviewed 12 experts and managers dealing with privacy and PETs in their daily business and identified incentives and hindrances to implement PETs from a business perspective (Harborth et al. 2018).

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Section: Discussionmentioning

confidence: 99%

Acceptance Factors of Privacy-Enhancing Technologies on the Basis of Tor and JonDonym

Pape

Harborth

2023

Human Factors in Privacy Research

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“…The most detailed analysis attempting to raise re-identification risks were proposed in [29][30][31]. Brasher [29] discussed the limitation of anonymization and encouraged its conjunction with pseudonymization to reduce the re-identification risks.…”

Section: Data Privacy-preserving Methodsmentioning

confidence: 99%

“…Li et al discussed the inference and de-anonymization risks within the driverless environment [30]. Löbner et al [31] evaluated the re-identification risks and impact within the vehicular context through a real test bed scenario, though the efforts remain limited to some of the privacypreserving techniques without reviewing them thoroughly.…”

Section: Data Privacy-preserving Methodsmentioning

confidence: 99%

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The Interface of Privacy and Data Security in Automated City Shuttles: The GDPR Analysis

et al. 2022

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The fast evolution and prevalence of driverless technologies has facilitated the testing and deployment of automated city shuttles (ACSs) as a means of public transportation in smart cities. For their efficient functioning, ACSs require a real-time data compilation and exchange of information with their internal components and external environment. However, that nexus of data exchange comes with privacy concerns and data protection challenges. In particular, the technical realization of stringent data protection laws on data collection and processing are key issues to be tackled within the ACSs ecosystem. Our work provides an in-depth analysis of the GDPR requirements that should be considered by the ACSs’ stakeholders during the collection, storage, use, and transmission of data to and from the vehicles. First, an analysis is performed on the data processing principles, the rights of data subjects, and the subsequent obligations for the data controllers where we highlight the mixed roles that can be assigned to the ACSs stakeholders. Secondly, the compatibility of privacy laws with security technologies focusing on the gap between the legal definitions and the technological implementation of privacy-preserving techniques are discussed. In face of the GDPR pitfalls, our work recommends a further strengthening of the data protection law. The interdisciplinary approach will ensure that the overlapping stakeholder roles and the blurring implementation of data privacy-preserving techniques within the ACSs landscape are efficiently addressed.

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“…Inferences can be seen as "new" data, created through the combination of (personal) data of different types and sources. Inferences can also be targeted at de-identified data [49,73] when combining the existing data set with another set to re-identify users. The ethical issue is now how these inferences should be treated under consideration of all circumstances, that is the different entities, creator, data subjects, involved, the type of data as well as its purpose and processing.…”

Section: The Value Of Data -Inferencesmentioning

confidence: 99%

A Discussion on Ethical Cybersecurity Issues in Digital Service Chains

Tronnier

Pape

Löbner

et al. 2022

Cybersecurity of Digital Service Chains

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Enabling cybersecurity and protecting personal data are crucial challenges in the development and provision of digital service chains. Data and information are the key ingredients in the creation process of new digital services and products. While legal and technical problems are frequently discussed in academia, ethical issues of digital service chains and the commercialization of data are seldom investigated. Thus, based on outcomes of the Horizon2020 PANELFIT project, this work discusses current ethical issues related to cybersecurity. Utilizing expert workshops and encounters as well as a scientific literature review, ethical issues are mapped on individual steps of digital service chains. Not surprisingly, the results demonstrate that ethical challenges cannot be resolved in a general way, but need to be discussed individually and with respect to the ethical principles that are violated in the specific step of the service chain. Nevertheless, our results support practitioners by providing and discussing a list of ethical challenges to enable legally compliant as well as ethically acceptable solutions in the future.

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Comparison of De-Identification Techniques for Privacy Preserving Data Analysis in Vehicular Data Sharing

Cited by 11 publications

References 25 publications

Acceptance Factors of Privacy-Enhancing Technologies on the Basis of Tor and JonDonym

Acceptance Factors of Privacy-Enhancing Technologies on the Basis of Tor and JonDonym

The Interface of Privacy and Data Security in Automated City Shuttles: The GDPR Analysis

A Discussion on Ethical Cybersecurity Issues in Digital Service Chains

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