Anomaly detection in data streams: The petrol station simulator

Anna Gorawska; Krzysztof Pasterak

doi:10.1007/978-3-319-34099-9_57

Anomaly detection in data streams: The petrol station simulator

Department of Applied Informatics (RAU/RAU7)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Developing anomaly detection systems requires diverse data for training and testing purposes. Real measurements are not necessarily reliable at this stage because it is almost impossible to find a diverse training set with exactly known characteristics. The petrol station simulator was designed to generate measurements that mimic real petrol station readings. The simulator produces datasets with exactly specified anomalies to be detected via anomaly detection system. The paper introduces foundations of the simulator with results. The discussion section presents future work in the area of stream data extraction and materialization in the Stream Data Warehouse.

Original language	English
Title of host publication	Beyond Databases, Architectures and Structures
Subtitle of host publication	Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings
Editors	Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bozena Malysiak-Mrozek, Daniel Kostrzewa
Publisher	Springer Verlag
Pages	727-736
Number of pages	10
ISBN (Print)	9783319340982
DOIs	https://doi.org/10.1007/978-3-319-34099-9_57
Publication status	Published - 2016
Event	12th International Conference on Beyond Databases, Architectures and Structures, BDAS 2016 - Ustron, Poland Duration: 31 May 2016 → 3 Jun 2016

Publication series

Name	Communications in Computer and Information Science
Volume	613
ISSN (Print)	1865-0929

Conference

Conference	12th International Conference on Beyond Databases, Architectures and Structures, BDAS 2016
Country/Territory	Poland
City	Ustron
Period	31/05/16 → 3/06/16

Keywords

Data stream
Fuel leak detection
Petrol station
Petrol station simulator
Sensor miscalibration
Statistical inventory reconciliation
Stream Data Warehouse
Stream data extraction

ASJC Scopus subject areas

General Computer Science
General Mathematics

Access to Document

10.1007/978-3-319-34099-9_57

Cite this

Gorawska, A., & Pasterak, K. (2016). Anomaly detection in data streams: The petrol station simulator. In S. Kozielski, D. Mrozek, P. Kasprowski, B. Malysiak-Mrozek, & D. Kostrzewa (Eds.), Beyond Databases, Architectures and Structures: Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings (pp. 727-736). (Communications in Computer and Information Science; Vol. 613). Springer Verlag. https://doi.org/10.1007/978-3-319-34099-9_57

Gorawska, Anna ; Pasterak, Krzysztof. / Anomaly detection in data streams : The petrol station simulator. Beyond Databases, Architectures and Structures: Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings. editor / Stanislaw Kozielski ; Dariusz Mrozek ; Pawel Kasprowski ; Bozena Malysiak-Mrozek ; Daniel Kostrzewa. Springer Verlag, 2016. pp. 727-736 (Communications in Computer and Information Science).

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abstract = "Developing anomaly detection systems requires diverse data for training and testing purposes. Real measurements are not necessarily reliable at this stage because it is almost impossible to find a diverse training set with exactly known characteristics. The petrol station simulator was designed to generate measurements that mimic real petrol station readings. The simulator produces datasets with exactly specified anomalies to be detected via anomaly detection system. The paper introduces foundations of the simulator with results. The discussion section presents future work in the area of stream data extraction and materialization in the Stream Data Warehouse.",

keywords = "Data stream, Fuel leak detection, Petrol station, Petrol station simulator, Sensor miscalibration, Statistical inventory reconciliation, Stream Data Warehouse, Stream data extraction",

author = "Anna Gorawska and Krzysztof Pasterak",

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Gorawska, A & Pasterak, K 2016, Anomaly detection in data streams: The petrol station simulator. in S Kozielski, D Mrozek, P Kasprowski, B Malysiak-Mrozek & D Kostrzewa (eds), Beyond Databases, Architectures and Structures: Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings. Communications in Computer and Information Science, vol. 613, Springer Verlag, pp. 727-736, 12th International Conference on Beyond Databases, Architectures and Structures, BDAS 2016, Ustron, Poland, 31/05/16. https://doi.org/10.1007/978-3-319-34099-9_57

Anomaly detection in data streams: The petrol station simulator. / Gorawska, Anna ; Pasterak, Krzysztof.
Beyond Databases, Architectures and Structures: Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings. ed. / Stanislaw Kozielski; Dariusz Mrozek; Pawel Kasprowski; Bozena Malysiak-Mrozek; Daniel Kostrzewa. Springer Verlag, 2016. p. 727-736 (Communications in Computer and Information Science; Vol. 613).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Anomaly detection in data streams

T2 - 12th International Conference on Beyond Databases, Architectures and Structures, BDAS 2016

AU - Gorawska, Anna

AU - Pasterak, Krzysztof

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - Developing anomaly detection systems requires diverse data for training and testing purposes. Real measurements are not necessarily reliable at this stage because it is almost impossible to find a diverse training set with exactly known characteristics. The petrol station simulator was designed to generate measurements that mimic real petrol station readings. The simulator produces datasets with exactly specified anomalies to be detected via anomaly detection system. The paper introduces foundations of the simulator with results. The discussion section presents future work in the area of stream data extraction and materialization in the Stream Data Warehouse.

AB - Developing anomaly detection systems requires diverse data for training and testing purposes. Real measurements are not necessarily reliable at this stage because it is almost impossible to find a diverse training set with exactly known characteristics. The petrol station simulator was designed to generate measurements that mimic real petrol station readings. The simulator produces datasets with exactly specified anomalies to be detected via anomaly detection system. The paper introduces foundations of the simulator with results. The discussion section presents future work in the area of stream data extraction and materialization in the Stream Data Warehouse.

KW - Data stream

KW - Fuel leak detection

KW - Petrol station

KW - Petrol station simulator

KW - Sensor miscalibration

KW - Statistical inventory reconciliation

KW - Stream Data Warehouse

KW - Stream data extraction

UR - https://www.scopus.com/pages/publications/84964703282

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DO - 10.1007/978-3-319-34099-9_57

M3 - Conference contribution

AN - SCOPUS:84964703282

SN - 9783319340982

T3 - Communications in Computer and Information Science

SP - 727

EP - 736

BT - Beyond Databases, Architectures and Structures

A2 - Kozielski, Stanislaw

A2 - Mrozek, Dariusz

A2 - Kasprowski, Pawel

A2 - Malysiak-Mrozek, Bozena

A2 - Kostrzewa, Daniel

PB - Springer Verlag

Y2 - 31 May 2016 through 3 June 2016

ER -

Gorawska A , Pasterak K. Anomaly detection in data streams: The petrol station simulator. In Kozielski S, Mrozek D, Kasprowski P, Malysiak-Mrozek B, Kostrzewa D, editors, Beyond Databases, Architectures and Structures: Advanced Technologies for Data Mining and Knowledge Discovery - 12th International Conference, BDAS 2016, Proceedings. Springer Verlag. 2016. p. 727-736. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-34099-9_57

Anomaly detection in data streams: The petrol station simulator

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Keywords

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