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Safeguarding Data Integrity by Cluster-Based Data Validation Network

  • Ensuring data quality is central to the digital transformation in industry. Business processes such as predictive maintenance or condition monitoring can be implemented or improved based on the available data. In order to guarantee high data quality, a single data validation system are usually used to validate the production data for further use. However, using a single system allows an attacker only to perform one successful attack to corrupt the whole system. We present a new approach in which a data validation system using multiple different validators minimizes the probability of success for the attacker. The validators are arranged in clusters based on their properties. For a validation process, a challenge is given that specifies which validators should perform the current validation. Validation results from other validators are dropped. This ensures that even for more than half of the validators being corrupted anomalies can be detected during the validation process.

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Metadaten
Author:Kevin Wallis, Fabian Schillinger, Christoph ReichORCiDGND, Christian Schindelhauer
DOI:https://doi.org/10.1109/WorldS4.2019.8904039
ISBN:978-1-7281-3780-3
Parent Title (English):Proceedings of the Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4), 30-31 July 2019, London, United Kingdom
Document Type:Conference Proceeding
Language:English
Year of Completion:2019
Release Date:2019/11/26
Tag:Big data; Cluster-based data validation; Data validation; Industrial internet of things; Internet of things
Pagenumber:9
Open Access:Innerhalb der Hochschule
Licence (German):License LogoEs gilt das UrhG