Detecting FNE in Sound Free-choice Petri Net with Data

Fang Zhao

doi:10.11648/j.ajomis.20190402.11

Abstract

Nowadays, the development of a third-party service (Express industry) and a third-party payment (Alipay) are very fast in online shopping. Despite there are many technologies to detect control flow errors in business process, the soundness verification in data flow is very hard. To support the design of a workflow, we usually consider the correct control flow structure. However, information about data flow should also be ensured correct. The operation of the system may suffer some external attacks, which makes the task change the read and write operations, which result in changing of control ﬂow structure which would lead to the emergence of unusual system. As a result, our approach provides a new technology to analysis the correctness of sound free-choice Petri net with data (SCDN). With the strong concealment of this attack, the system may suffer false-negative data ﬂow errors (FNE), which would bring some loses to the participants. On the basis of behavioral proﬁles (BP), redundant data ﬂow errors (RDE) and missing data ﬂow errors (MDE), we provide the theory of FNE to demonstrate the stability, effectiveness and adaptation of our detection methods. Finally, a real E-commerce business system is used to illustrate the practicability of the method provided in this paper.

Highlights

IntroductionThe Internet technology has been widely used in stimulating the growth of E-commerce
In recent years, the Internet technology has been widely used in stimulating the growth of E-commerce
The contribution of this paper is mainly embodied in the following aspects: Firstly, we define the sound free-choice Petri nets, weak order relation, behavioral profile; Secondly, we give some definitions about the data flow, like read and write operations, redundant data flow errors and missing data flow errors, we use them to detect false negative data flow errors

Summary

Introduction

The Internet technology has been widely used in stimulating the growth of E-commerce. Meda and Anup Kumar Sen provide missing data flow errors, inconsistent data flow errors, lost data flow errors and redundant data flow errors and present a graph traversal algorithm called GTforDF for detecting data flow errors in unstructured and nested workflow, illustrate the operation on realistic examples [21] This was different from the theory provided by Sherry X. The contribution of this paper is mainly embodied in the following aspects: Firstly, we define the sound free-choice Petri nets, weak order relation, behavioral profile; Secondly, we give some definitions about the data flow, like read and write operations, redundant data flow errors and missing data flow errors, we use them to detect false negative data flow errors.

Preliminaries

Data Flow Anomaly Detection Technology

Case Study

Findings

Conclusions and Future Works