Unleashing The Potential of Data Ecosystems: Establishing Digital Trust through Trust-Enhancing Technologies

2023 | European Conference On Information Systems | Citations: 0

Authors: Schäfer, Fabian; Rosen, Jeremy; Zimmermann, Christian; Wortmann, Felix

Abstract: Companies increasingly innovate data-driven business models, enabling them to c ... Expand

Abstract: Companies increasingly innovate data-driven business models, enabling them to create new products and services. Emerging data ecosystems provide these companies access to complementary data, offering them additional potential. This, however remains untapped, as a lack of digital trust prevents companies from sharing data within these ecosystems. By using trust-enhancing technologies, companies can establish trust; this can be explained through the theoretical lens of system trust. Using a design science research approach helped us to unlock the knowledge of 21 experts and identify five technologies with the potential to solve the trust challenge: self-sovereign identities, differential privacy, fully homomorphic encryption, trusted execution environments and secure multiparty computation. We integrated these technologies into the data sharing process in data ecosystems and elaborated on their limitations and maturity. Ultimately, we derived two principles that allow for adapting our results to future technological developments: complementarity and customization. Collapse

Topics: digital ecosystem differential privacy fully homomorphic encryption distributed ledger technology data encryption

Methods: design science qualitative interview design artifact design requirement design process

MEDIATING THE TENSION BETWEEN DATA SHARING AND PRIVACY: THE CASE OF DMA AND GDPR

2023 | European Conference On Information Systems | Citations: 0

Authors: Weigl, Linda; Barbereau, Tom; Sedlmeir, Johannes; Zavolokina, Liudmila

Abstract: The Digital Markets Act (DMA) constitutes a crucial part of the European legisl ... Expand

Abstract: The Digital Markets Act (DMA) constitutes a crucial part of the European legislative framework addressing the dominance of 'Big Tech'. It intends to foster fairness and competition in Europe's digital platform economy by imposing obligations on 'gatekeepers' to share end-user-related information with business users. Yet, this may involve the processing of personal data subject to the General Data Protection Regulation (GDPR). The obligation to provide access to personal data in a GDPR-compliant manner poses a regulatory and technical challenge and can serve as a justification for gatekeepers to refrain from data sharing. In this research-in-progress paper, we analyze key tensions between the DMA and the GDPR through the paradox perspective. We argue through a task-technology fit approach how privacyenhancing technologies -particularly anonymization techniques -and portability could help mediate tensions between data sharing and privacy. Our contribution provides theoretical and practical insights to facilitate legal compliance. Collapse

Topics: legal context General Data Protection Regulation privacy differential privacy data protection

Methods: decision tree classification structured literature research computational algorithm synthesis qualitative interview

Theories: theory of task technology fit

On achieving secure collaboration in supply chains

2015 | Information Systems Frontiers | Citations: 1

Authors: Barkataki, Sharad; Zeineddine, Hassan

Abstract: Security of private information is a critical requirement for information sharin ... Expand

Abstract: Security of private information is a critical requirement for information sharing in supply chains. Security is measured on a variety of metrics: participating suppliers in a supply chain process need guarantees on confidentiality, anonymity, and privacy; the purchaser needs assurance on verifiability and non-repudiation. Given the mutually exclusive nature of security metrics such as anonymity vs. non-repudiation, and confidentiality vs. verifiability, the challenge is to design a process that satisfies all these metrics. In this paper, we propose three major processes that enable secure information sharing and secure computation of arbitrary supply chain functions. We evaluate and compare the secure processes using a ranking method and score function, which we propose for that purpose. We find that certain processes will be preferred over other processes, depending on the environmental characteristics and user preferences. Thus, our secure processes aim to solve major collaboration issues in supply chains. Collapse

Topics: supply chain management privacy anonymity data encryption information exchange

Methods: literature study computational algorithm optimization model machine learning

Confidential Information-Sharing for Automated Sustainability Benchmarks

2011 | International Conference on Information Systems | Citations: 0

Authors: Kerschbaum, Florian; StrÃ, Jens

Abstract: The pressure on enterprises to manage and improve their environmental sustainabi ... Expand

Abstract: The pressure on enterprises to manage and improve their environmental sustainability is steadily increasing. Despite the growing awareness in the IS community and business practice, current IS solutions remain in an initial state. Sustainability benchmarking is seen as a novel and effective tool in this context. However, sustainability benchmarking faces two major obstacles: First, the heterogeneity of the data requires significant pre-processing, and, second, the sensitivity of the data causes enterprises to reluctantly share this data. Our contribution is twofold: After analyzing the data input problem and identifying appropriate and available solutions, we present a secure sustainability benchmarking service (SBS) to overcome the information-sharing problem. Our service uses homomorphic encryption to protect the data during processing and differential privacy to protect against leakages from the reports. Finally, we evaluate in detail a prototypical implementation of this secure sustainability benchmarking service and illustrate its applicability in industry. Collapse

Topics: data encryption supply chain management enterprise resource planning homomorphic encryption public key encryption

Methods: design artifact experiment company material computational algorithm data envelopment analysis

Secure and Sustainable Benchmarking in Clouds: A Multi-Party Cloud Application with an Untrusted Service Provider

2011 | Business & Information Systems Engineering | Citations: 0

Authors: Kerschbaum, Florian

Abstract: Cloud computing entails a novel security threat: The cloud service provider is ... Expand

Abstract: Cloud computing entails a novel security threat: The cloud service provider is entrusted with the data of all its customers. Encryption may provide the solution. Using the example of collaborative benchmarking the authors present and evaluate the exemplary design and implementation that operates on encrypted data. Collapse

Topics: cloud computing homomorphic encryption Java data encryption web service

Methods: experiment cluster analysis computational algorithm time series analysis longitudinal research