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Authors: Alfredo Cuzzocrea 1 ; Assaf Schuster 2 and Gianni Vercelli 3

Affiliations: 1 University of Trieste and ICAR-CNR, Italy ; 2 Technion, Israel ; 3 University of Genoa, Italy

Keyword(s): Privacy-Preserving OLAP over Data Streams, OLAP-based Monitoring of Data Streams, Privacy-Preserving OLAP-based Monitoring of Data Streams.

Related Ontology Subjects/Areas/Topics: Data Warehouses and OLAP ; Databases and Information Systems Integration ; Distributed Database Systems ; Enterprise Information Systems

Abstract: 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 privacypreserving 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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Cuzzocrea, A.; Schuster, A. and Vercelli, G. (2018). PP-OMDS: An Effective and Efficient Framework for Supporting Privacy-Preserving OLAP-based Monitoring of Data Streams. In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-298-1; ISSN 2184-4992, SciTePress, pages 282-292. DOI: 10.5220/0006812102820292

@conference{iceis18,
author={Alfredo Cuzzocrea. and Assaf Schuster. and Gianni Vercelli.},
title={PP-OMDS: An Effective and Efficient Framework for Supporting Privacy-Preserving OLAP-based Monitoring of Data Streams},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2018},
pages={282-292},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006812102820292},
isbn={978-989-758-298-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - PP-OMDS: An Effective and Efficient Framework for Supporting Privacy-Preserving OLAP-based Monitoring of Data Streams
SN - 978-989-758-298-1
IS - 2184-4992
AU - Cuzzocrea, A.
AU - Schuster, A.
AU - Vercelli, G.
PY - 2018
SP - 282
EP - 292
DO - 10.5220/0006812102820292
PB - SciTePress