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Insuring Sensitive Processes through Process Mining Jorge Munoz-Gama Isao Echizen Jorge Munoz-Gama and Isao Echizen

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Insuring Sensitive Processes through Process Mining

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Insuring Scenario Insurance Company 3 Clients Service Provider ProcessesObjectsData

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Insuring Sensitive Processes through Process Mining

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What is a Process? 5 ABCDEF

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Insuring Sensitive Processes through Process Mining

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Process Mining in a Nutshell 7 THEORYREALITY

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Process Mining in a Nutshell 8 THEORYREALITY REALITY REFLECTION LOGS

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Process Mining Process mining is a process management technique that allows for the analysis of processes based on real event logs, and using formal models. Process Mining: Discovery, Conformance and Enhancement of Business Processes by W.M.P. van der Aalst, Springer Verlag, 2011 (ISBN 978-3-642-19344-6). 9

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Process Mining: Discovery, Conformance and Enhancement 10

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Process Mining: Discovery, Conformance and Enhancement 11

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Process Mining: Discovery, Conformance and Enhancement Info 1 Info1aInfo1b Info 2 Info2aInfo2b 12

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Insurance Schema

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Insurance Policy Architecture for Insuring Processes Formal Model as Policy Formalism and non ambiguity Variety of widely used model formalism: Petri nets, EPC, BPMN, BPEL, YAWL, Graphical representation for an easy comprehension Wide range of formal techniques and software 14

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Insurance Policy Architecture for Insuring Processes 15

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Insurance Cycle based on Process Mining

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Insurance Cycle 17

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Modeling Alpha Miner Alpha ++ Genetic Miner Fuzzy Miner Genet ILMiner 18 Process Mining DISCOVERY

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Modeling (Example) 19

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Petri Nets in a nutshell 20

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Validation 21 Validate with know benchmarks The results are compared with the expected values Comparison not trivial because non model-driven execution Fitness based on alignments A* algorithm to find the optimal path on the model corresponding to each case Based on costs Process Mining CONFORMANCE * A. Adriansyah, B. F. van Dongen, and W. M. P. van der Aalst, Conformance checking using cost-based fitness analysis, in EDOC.

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Validation 22 Optimal Alignment Execution

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Forensic 23 A- posteriori Each trace = claim Same fitness conformance technique as before (based on alignments) Locate where the problem is and who is accountable

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Forensic 24 Optimal Alignment Claim

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Forensic 25

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Re-design 26 Insurance Company not want to expose to much risk, i.e., insure the real process and only the real process (not all possible situations) The real process may change with the time (Concept Drifting) so the policy agreement Conformance techniques to assess how precise is the model Precision dimension Based on escaping points Points where the model allows more behavior than the one reflected in the log Process Mining CONFORMANCE * J. Munoz-Gama and J. Carmona, A fresh look at precision in process conformance in BPM,.

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Re-design 27

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Implementation (ProM) Main Tool for Process Mining Extensible with plug-ins Platform independent Open-source and free Widely used by the industry and the researchers 28 http://www.promtools.org/prom6/

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Discovery Implementation 29 Alpha, Genetic, ILPMiner,

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Fitness Implementation PNetReplayer Package 30

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Precision Implementation ETConformance Package 31

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Conclusions and Future Work Insurance of Processes based on Process Mining Schema Based on Formal Model as Policy Cycle of insurance: modeling, validation, forensic and redesign Not only control flow dimension Other dimensions: roles, performance time, social organization, 32

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More Information 33 Process Mining: Discovery, Conformance and Enhancement of Business Processes by W.M.P. van der Aalst, Springer Verlag, 2011 (ISBN 978-3-642-19344-6). Insuring Sensitive Processes through Process Mining Jorge Munoz-Gama and Isao Echizen Autonomic and Trusted Computing (ATC) 2012

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Questions?

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Thank You

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Illustrative Example: Intro Online company providing a service to buy and sell cars between users Collect pictures and videos of the cars and distribute this contents to other users The sensitive process to be insured: the anonymization of the pictures and videos 36