Algorithms for anomaly detection of traces in logs of process aware information systems

被引：74

作者：

Bezerra, Fabio ^{[1
]}

Wainer, Jacques ^{[2
]}

机构：

[1] Univ Fed Rural Amazonia, Cyberspace Inst, Belem, Para, Brazil

[2] Univ Estadual Campinas, Inst Comp, Campinas, SP, Brazil

来源：

INFORMATION SYSTEMS | 2012年 / 38卷 / 01期

关键词：

Anomaly detection; Process mining; Process-aware systems; PROCESS MODELS; WORKFLOW MODELS; EXECUTIONS; FRAMEWORK; CHECKING; ISSUES; FRAUD;

D O I：

10.1016/j.is.2012.04.004

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (c) 2012 Elsevier Ltd. All rights reserved.

引用

页码：33 / 44

页数：12

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