Detecting FNE in Sound Free-choice Petri Net with Data

Fang Zhao

doi:doi:10.11648/j.ajomis.20190402.11

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Detecting FNE in Sound Free-choice Petri Net with Data

Fang Zhao

Published in American Journal of Operations Management and Information Systems (Volume 4, Issue 2)

Received: 24 April 2019 Accepted: 29 May 2019 Published: 12 June 2019

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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.

Published in	American Journal of Operations Management and Information Systems (Volume 4, Issue 2)
DOI	10.11648/j.ajomis.20190402.11
Page(s)	48-56
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

SCDN, FNE, BP, RDE, MDE

References

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APA Style

Fang Zhao. (2019). Detecting FNE in Sound Free-choice Petri Net with Data. American Journal of Operations Management and Information Systems, 4(2), 48-56. https://doi.org/10.11648/j.ajomis.20190402.11

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ACS Style

Fang Zhao. Detecting FNE in Sound Free-choice Petri Net with Data. Am. J. Oper. Manag. Inf. Syst. 2019, 4(2), 48-56. doi: 10.11648/j.ajomis.20190402.11

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AMA Style

Fang Zhao. Detecting FNE in Sound Free-choice Petri Net with Data. Am J Oper Manag Inf Syst. 2019;4(2):48-56. doi: 10.11648/j.ajomis.20190402.11

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@article{10.11648/j.ajomis.20190402.11,
  author = {Fang Zhao},
  title = {Detecting FNE in Sound Free-choice Petri Net with Data},
  journal = {American Journal of Operations Management and Information Systems},
  volume = {4},
  number = {2},
  pages = {48-56},
  doi = {10.11648/j.ajomis.20190402.11},
  url = {https://doi.org/10.11648/j.ajomis.20190402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/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.},
 year = {2019}
}

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TY  - JOUR
T1  - Detecting FNE in Sound Free-choice Petri Net with Data
AU  - Fang Zhao
Y1  - 2019/06/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ajomis.20190402.11
DO  - 10.11648/j.ajomis.20190402.11
T2  - American Journal of Operations Management and Information Systems
JF  - American Journal of Operations Management and Information Systems
JO  - American Journal of Operations Management and Information Systems
SP  - 48
EP  - 56
PB  - Science Publishing Group
SN  - 2578-8310
UR  - https://doi.org/10.11648/j.ajomis.20190402.11
AB  - 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.
VL  - 4
IS  - 2
ER  -

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Author Information

Fang Zhao

Department of Computer Science, Tongji University, Shanghai, China

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APA Style

Fang Zhao. (2019). Detecting FNE in Sound Free-choice Petri Net with Data. American Journal of Operations Management and Information Systems, 4(2), 48-56. https://doi.org/10.11648/j.ajomis.20190402.11

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ACS Style

Fang Zhao. Detecting FNE in Sound Free-choice Petri Net with Data. Am. J. Oper. Manag. Inf. Syst. 2019, 4(2), 48-56. doi: 10.11648/j.ajomis.20190402.11

Copy | Download

AMA Style

Fang Zhao. Detecting FNE in Sound Free-choice Petri Net with Data. Am J Oper Manag Inf Syst. 2019;4(2):48-56. doi: 10.11648/j.ajomis.20190402.11

Copy | Download

@article{10.11648/j.ajomis.20190402.11,
  author = {Fang Zhao},
  title = {Detecting FNE in Sound Free-choice Petri Net with Data},
  journal = {American Journal of Operations Management and Information Systems},
  volume = {4},
  number = {2},
  pages = {48-56},
  doi = {10.11648/j.ajomis.20190402.11},
  url = {https://doi.org/10.11648/j.ajomis.20190402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Detecting FNE in Sound Free-choice Petri Net with Data
AU  - Fang Zhao
Y1  - 2019/06/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ajomis.20190402.11
DO  - 10.11648/j.ajomis.20190402.11
T2  - American Journal of Operations Management and Information Systems
JF  - American Journal of Operations Management and Information Systems
JO  - American Journal of Operations Management and Information Systems
SP  - 48
EP  - 56
PB  - Science Publishing Group
SN  - 2578-8310
UR  - https://doi.org/10.11648/j.ajomis.20190402.11
AB  - 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.
VL  - 4
IS  - 2
ER  -

Copy | Download