TY - GEN
T1 - ImputAnom
T2 - 25th International Conference on Information Integration and Web Intelligence, iiWAS 2023
AU - Fatyanosa, Tirana Noor
AU - Data, Mahendra
AU - Firdausanti, Neni Alya
AU - Prayoga, Putu Hangga Nan
AU - Mendonça, Israel
AU - Aritsugi, Masayoshi
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Anomaly detection plays a crucial role in various domains such as cybersecurity, fraud detection, and industrial asset condition monitoring. In these fields, identifying abnormal patterns or outliers is paramount for the business they support. This paper presents a new framework that utilizes imputation methods to effectively identify anomalies. To evaluate the performance of the proposed framework, experiments were conducted on different datasets that contain anomalies from different domains. Experimental results demonstrate the effectiveness of the framework in helping to detect anomalies. It provides improvements between 8.17% and 165.21% for all datasets. Experimental results also confirm the effectiveness of the proposed framework and its potential to be applied in real-world scenarios.
AB - Anomaly detection plays a crucial role in various domains such as cybersecurity, fraud detection, and industrial asset condition monitoring. In these fields, identifying abnormal patterns or outliers is paramount for the business they support. This paper presents a new framework that utilizes imputation methods to effectively identify anomalies. To evaluate the performance of the proposed framework, experiments were conducted on different datasets that contain anomalies from different domains. Experimental results demonstrate the effectiveness of the framework in helping to detect anomalies. It provides improvements between 8.17% and 165.21% for all datasets. Experimental results also confirm the effectiveness of the proposed framework and its potential to be applied in real-world scenarios.
KW - Anomaly detection
KW - Imputation
UR - http://www.scopus.com/inward/record.url?scp=85178662883&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-48316-5_8
DO - 10.1007/978-3-031-48316-5_8
M3 - Conference contribution
AN - SCOPUS:85178662883
SN - 9783031483158
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 56
EP - 61
BT - Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings
A2 - Delir Haghighi, Pari
A2 - Pardede, Eric
A2 - Dobbie, Gillian
A2 - Yogarajan, Vithya
A2 - ER, Ngurah Agus Sanjaya
A2 - Kotsis, Gabriele
A2 - Khalil, Ismail
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 4 December 2023 through 6 December 2023
ER -