A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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  • Project Holi
  • Universita Mediterranea di Reggio Calabria
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OriginalspracheEnglisch
Titel des SammelwerksApplied Intelligence and Informatics
UntertitelSecond International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings
Herausgeber/-innenMufti Mahmud, Cosimo Ieracitano, Nadia Mammone, Francesco Carlo Morabito, M. Shamim Kaiser
Herausgeber (Verlag)Springer Science and Business Media Deutschland GmbH
Seiten511-522
Seitenumfang12
ISBN (elektronisch)978-3-031-24801-6
ISBN (Print)9783031248009
PublikationsstatusVeröffentlicht - 2 Feb. 2023
Veranstaltung2nd International Conference on Applied Intelligence and Informatics, AII 2022 - Reggio Calabria, Italien
Dauer: 1 Sept. 20223 Sept. 2022

Publikationsreihe

NameCommunications in Computer and Information Science
Band1724 CCIS
ISSN (Print)1865-0929
ISSN (elektronisch)1865-0937

Abstract

Anomaly detection is an important task in many fields such as eHealth and online fraud. In this paper, we propose a new technique for anomaly detection based on a graph that connects transactions with the same attribute values and searches for dense clusters indicative of an anomalous pattern. The experimental evaluation shows that the graph-based approach outperforms two other approaches in the considered dataset. The extension of this approach to the eHealth domain is reserved as future work.

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A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values. / Brauer, Steffen; Fisichella, Marco; Lax, Gianluca et al.
Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings. Hrsg. / Mufti Mahmud; Cosimo Ieracitano; Nadia Mammone; Francesco Carlo Morabito; M. Shamim Kaiser. Springer Science and Business Media Deutschland GmbH, 2023. S. 511-522 (Communications in Computer and Information Science; Band 1724 CCIS).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Brauer, S, Fisichella, M, Lax, G, Romeo, C & Russo, A 2023, A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values. in M Mahmud, C Ieracitano, N Mammone, FC Morabito & MS Kaiser (Hrsg.), Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings. Communications in Computer and Information Science, Bd. 1724 CCIS, Springer Science and Business Media Deutschland GmbH, S. 511-522, 2nd International Conference on Applied Intelligence and Informatics, AII 2022, Reggio Calabria, Italien, 1 Sept. 2022. https://doi.org/10.1007/978-3-031-24801-6_36
Brauer, S., Fisichella, M., Lax, G., Romeo, C., & Russo, A. (2023). A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values. In M. Mahmud, C. Ieracitano, N. Mammone, F. C. Morabito, & M. S. Kaiser (Hrsg.), Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings (S. 511-522). (Communications in Computer and Information Science; Band 1724 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-24801-6_36
Brauer S, Fisichella M, Lax G, Romeo C, Russo A. A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values. in Mahmud M, Ieracitano C, Mammone N, Morabito FC, Kaiser MS, Hrsg., Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. S. 511-522. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-24801-6_36
Brauer, Steffen ; Fisichella, Marco ; Lax, Gianluca et al. / A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values. Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings. Hrsg. / Mufti Mahmud ; Cosimo Ieracitano ; Nadia Mammone ; Francesco Carlo Morabito ; M. Shamim Kaiser. Springer Science and Business Media Deutschland GmbH, 2023. S. 511-522 (Communications in Computer and Information Science).
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abstract = "Anomaly detection is an important task in many fields such as eHealth and online fraud. In this paper, we propose a new technique for anomaly detection based on a graph that connects transactions with the same attribute values and searches for dense clusters indicative of an anomalous pattern. The experimental evaluation shows that the graph-based approach outperforms two other approaches in the considered dataset. The extension of this approach to the eHealth domain is reserved as future work.",
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N1 - Funding Information: Acknowledgements. This work was partially supported by “iCARE” project (CUP J39J14001400007) - action 10.5.12 - funded within POR FESR FSE 2014/2020 of Calabria Region with the participation of European Community Resources of FESR and FSE, of Italy and of Calabria.

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