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Privacy-preserving Distributed Analytics: Addressing the Privacy-Utility Tradeoff Using Homomorphic Encryption for Peer-to-Peer Analytics

2015 | International Conference on Information Systems | Citations: 0
Authors: Bhattacharya, Prasanta; Phan, Tuan; Liu, Linlin

Abstract: Data is becoming increasingly valuable, but concerns over its security and priva ... Expand

Abstract: Data is becoming increasingly valuable, but concerns over its security and privacy have limited its utility in analytics. Researchers and practitioners are constantly facing a privacy-utility tradeoff where addressing the former is often at the cost of the data utility and accuracy. In this paper, we draw upon mathematical properties of partially homomorphic encryption, a form of asymmetric key encryption scheme, to transform raw data from multiple sources into secure, yet structure-preserving encrypted data for use in statistical models, without loss of accuracy. We contribute to the literature by: i) proposing a method for secure and privacy-preserving analytics and illustrating its utility by implementing a secure and privacy-preserving version of Maximum Likelihood Estimator, “s-MLE”, and ii) developing a web-based framework for privacy-preserving peer-to-peer analytics with distributed datasets. Our study has widespread applications in sundry industries including healthcare, finance, ecommerce etc., and has multi-faceted implications for academics, businesses, and governments. Collapse

Semantic filters: partially homomorphic encryption

Topics: data encryption privacy public key encryption peer-to-peer model homomorphic encryption

Methods: logistic regression simulation design artifact conceptual modelling design science
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

Semantic filters: partially homomorphic encryption

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
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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

Semantic filters: partially homomorphic encryption

Topics: cloud computing homomorphic encryption Java data encryption web service

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

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Privacy-preserving Distributed Analytics: Addressing the Privacy-Utility Tradeoff Using Homomorphic Encryption for Peer-to-Peer Analytics

Confidential Information-Sharing for Automated Sustainability Benchmarks

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