TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Wallis, Kevin
A1  - Schillinger, Fabian
A1  - Reich, Christoph
A1  - Schindelhauer, Christian
T1  - Safeguarding Data Integrity by Cluster-Based Data Validation Network
T2  - Proceedings of the Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4), 30-31 July 2019, London, United Kingdom
N2  - 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.
KW  - Industrial internet of things
KW  - Internet of things
KW  - Data validation
KW  - Cluster-based data validation
KW  - Big data
Y1  - 2019
SN  - 978-1-7281-3780-3
SB  - 978-1-7281-3780-3
U6  - https://doi.org/10.1109/WorldS4.2019.8904039
DO  - https://doi.org/10.1109/WorldS4.2019.8904039
SP  - 9
S1  - 9
ER  -