Privacy-Preserving OLAP-Based Monitoring of Data Streams: The PP-OMDS Approach.
Alfredo Cuzzocrea, Assaf Schuster, Gianni Vercelli, Massimiliano Nolich · CINECA IRIS Institutial Research Information System (University of Genoa) · 2019
In this paper, we propose PP-OMDS (Privacy-Preserving OLAP-based Monitoring of Data Streams), an innovative framework for supporting the OLAP-based monitoring of data streams, which is relevant for a plethora of application scenarios (e.g., security, emergency management, and so forth), in a privacy-preserving manner. The paper describes motivations, principles and achievements of the PP-OMDS framework, along with technological advancements and innovations. We also incorporate a detailed comparative analysis with competitive frameworks, along with a trade-off analysis.