Details
| Original language | English |
|---|---|
| Title of host publication | Applied Intelligence and Informatics |
| Subtitle of host publication | Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings |
| Editors | Mufti Mahmud, Cosimo Ieracitano, Nadia Mammone, Francesco Carlo Morabito, M. Shamim Kaiser |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 511-522 |
| Number of pages | 12 |
| ISBN (electronic) | 978-3-031-24801-6 |
| ISBN (print) | 9783031248009 |
| Publication status | Published - 2 Feb 2023 |
| Event | 2nd International Conference on Applied Intelligence and Informatics, AII 2022 - Reggio Calabria, Italy Duration: 1 Sept 2022 → 3 Sept 2022 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 1724 CCIS |
| ISSN (Print) | 1865-0929 |
| ISSN (electronic) | 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.
Keywords
- Anomaly detection, Fraud detection, Outlier detection
ASJC Scopus subject areas
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Applied Intelligence and Informatics: Second International Conference, AII 2022, Reggio Calabria, Italy, September 1–3, 2022, Proceedings. ed. / Mufti Mahmud; Cosimo Ieracitano; Nadia Mammone; Francesco Carlo Morabito; M. Shamim Kaiser. Springer Science and Business Media Deutschland GmbH, 2023. p. 511-522 (Communications in Computer and Information Science; Vol. 1724 CCIS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values
AU - Brauer, Steffen
AU - Fisichella, Marco
AU - Lax, Gianluca
AU - Romeo, Carlo
AU - Russo, Antonia
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.
PY - 2023/2/2
Y1 - 2023/2/2
N2 - 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.
AB - 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.
KW - Anomaly detection
KW - Fraud detection
KW - Outlier detection
UR - http://www.scopus.com/inward/record.url?scp=85149692967&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-24801-6_36
DO - 10.1007/978-3-031-24801-6_36
M3 - Conference contribution
AN - SCOPUS:85149692967
SN - 9783031248009
T3 - Communications in Computer and Information Science
SP - 511
EP - 522
BT - Applied Intelligence and Informatics
A2 - Mahmud, Mufti
A2 - Ieracitano, Cosimo
A2 - Mammone, Nadia
A2 - Morabito, Francesco Carlo
A2 - Kaiser, M. Shamim
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Applied Intelligence and Informatics, AII 2022
Y2 - 1 September 2022 through 3 September 2022
ER -