TY - GEN
T1 - From Network Traffic Data to Business Activities
T2 - 22nd International Conference on Business Process Modeling, Development and Support, BPMDS 2021 and 26th International Conference on Exploring Modeling Methods for Systems Analysis and Development, EMMSAD 2021 Held at CAiSE 2021
AU - Engelberg, Gal
AU - Hadad, Moshe
AU - Soffer, Pnina
N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Event logs are the main source for business process mining techniques. However, they are produced by part of the systems and are not always available. Furthermore, logs that are created by a given information system may not span the full process, which may entail actions performed outside the system. We suggest that data generated by communication network traffic associated with the process can fill this gap, both in availability and in span. However, traffic data is technically oriented and noisy, and there is a huge conceptual gap between this data and business meaningful event logs. Addressing this gap, this work develops a conceptual model of traffic behavior in a business activity. To develop the model, we use simulated traffic data annotated by the originating activity and perform an iterative process of abstracting and filtering the data, along with application of process discovery. The results include distinct process models for each activity type and a generic higher-level model of traffic behavior in a business activity. Conformance checking used for evaluating the models shows high fitness and generalization across different organizational domains.
AB - Event logs are the main source for business process mining techniques. However, they are produced by part of the systems and are not always available. Furthermore, logs that are created by a given information system may not span the full process, which may entail actions performed outside the system. We suggest that data generated by communication network traffic associated with the process can fill this gap, both in availability and in span. However, traffic data is technically oriented and noisy, and there is a huge conceptual gap between this data and business meaningful event logs. Addressing this gap, this work develops a conceptual model of traffic behavior in a business activity. To develop the model, we use simulated traffic data annotated by the originating activity and perform an iterative process of abstracting and filtering the data, along with application of process discovery. The results include distinct process models for each activity type and a generic higher-level model of traffic behavior in a business activity. Conformance checking used for evaluating the models shows high fitness and generalization across different organizational domains.
KW - Conceptual modeling
KW - Network traffic
KW - Process discovery
UR - http://www.scopus.com/inward/record.url?scp=85111868908&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-79186-5_1
DO - 10.1007/978-3-030-79186-5_1
M3 - Conference contribution
SN - 9783030791858
T3 - Lecture Notes in Business Information Processing
SP - 3
EP - 18
BT - Enterprise, Business-Process and Information Systems Modeling - 22nd International Conference, BPMDS 2021, and 26th International Conference, EMMSAD 2021, Held at CAiSE 2021, Proceedings
A2 - Augusto, Adriano
A2 - Gill, Asif
A2 - Nurcan, Selmin
A2 - Reinhartz-Berger, Iris
A2 - Schmidt, Rainer
A2 - Zdravkovic, Jelena
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 28 June 2021 through 29 June 2021
ER -