Anomaly Detection Model Over Blockchain Electronic Transactions

Sirine SAYADI, Sonia BEN REJEB, Zied CHOUKAIR
2019 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)  
Electronic transactions with cryptocurrency systems based on blockchain in our days have become very popular due to the good reputation of this technology. However, that good reputation cannot deny the serious anomalies and the risks that can cause these cryptocurrencies. In this work, we propose a new model for anomaly detection over bitcoin electronic transactions. We used in our proposal two machine learning algorithms, namely the One Class Support Vector Machines (OCSVM) algorithm to detect
more » ... algorithm to detect outliers and the K-Means algorithm in order to group the similar outliers with the same type of anomalies. We evaluated our work by generating detection results and we obtained high performance results on accuracy.
doi:10.1109/iwcmc.2019.8766765 dblp:conf/iwcmc/SayadiRC19 fatcat:zmelhhqo7bbztcdgntdezdm6te