Algorithms for anomaly detection of traces in logs of process aware information systems
This paper discusses four algorithms for detecting anomalies in logs of process aware systems.One of the algorithms only marks as potential anomalies traces that are infrequent in the log.The other three algorithms:threshold,iterative and sampling are based on mining a process model from the log,or a subset of it.The algorithms were evaluated on a set of 1500 artificial logs,with different profiles on the number of anomalous traces and the number of times each anomalous traces was present in the log.The sampling algorithm proved to be the most effective solution.We also applied the algorithm to a real log,and compared the resulting detected anomalous traces with the ones detected by a different procedure that relies on manual choices.
Anomaly detection Process mining Process-aware systems
Fabio Bezerra Jacques Wainer
Cyberspace Institute-UFRA,Av.Presidente Tancredo Neves,2501Bele”m,Para,Brazil Institute of Computing-UNICAMP,Av.Albert Einstein,1251 Campinas,Sao Paulo,Brazil
国内会议
南京
英文
1-12
2013-11-01（万方平台首次上网日期，不代表论文的发表时间）