Cybersecurity Analysis via Process Mining: A Systematic Literature Review

Macák, Martin; Daubner, Lukáš; Sani, Mohammadreza Fani; Bühnová, Barbora

doi:10.1007/978-3-030-95405-5_28

Cited by 6 publications

(3 citation statements)

References 59 publications

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“…Process mining is a relatively young discipline that has exponentially advanced in recent years. Since its inception, it has been applied in a wide range of industries, including healthcare [11], security [12], telecommunications [13], education [14], software [15], and aviation [16], among others [17]. This has permitted the development of specialized software, both commercial-e.g., Celonis, Disco, Minit-and open-source-e.g., ProM, BupaR, pm4py- [18].…”

Section: Process Mining In the Mining Industrymentioning

confidence: 99%

Towards the Application of Process Mining in the Mining Industry—An LHD Maintenance Process Optimization Case Study

et al. 2023

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Inefficiencies in mine equipment maintenance processes result in high operation costs and reduce mine sustainability. However, current methods for process optimization are limited due to a lack of access to structured data. This research aims to test the hypothesis that process mining techniques can be used to optimize workflow for mine equipment maintenance processes using low-level data. This is achieved through a process-oriented analysis where low-level data are processed as an event log and used as input for a developed process model. We present a Discrete-Event Simulation of the maintenance process to generate an event log from low-level data and analyze the process with process mining. A case study of the maintenance process in an underground block caving mine is used to gain operational insight. The diagnosis of the mine’s maintenance process showed a loss of 23,800 equipment operating hours per year, with a non-production cost of about 1.12 MUSD/year. Process mining obtained a non-biased representation of the maintenance process and aided in identifying bottlenecks and inefficiencies in the equipment maintenance processes.

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Section: Process Mining In the Mining Industrymentioning

confidence: 99%

Towards the Application of Process Mining in the Mining Industry—An LHD Maintenance Process Optimization Case Study

et al. 2023

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“…Based on the extracted knowledge from event data (i.e., event logs) produced by information systems, PM is mainly used to analyze, discover, and enhance processes [48][49][50]. PM has been successfully applied in various areas, including software engineering [51,52]. Therefore, process mining techniques are applied to find development processes using publicly available, open-source, software development repositories [53]; in another study, a process mining framework was used to discover software development processes from the event logs generated by software configuration management (SCM) systems [54].…”

Section: Conformance Checkingmentioning

confidence: 99%

Analysis, Evaluation and Reusability of Virtual Laboratory Software Based on Conceptual Modeling and Conformance Checking

Sypsas

Kalles

2023

Mathematics

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Virtual laboratories have been increasingly used in tertiary education for natural and applied sciences, especially due to the COVID pandemic, generating a substantial investment in corresponding software applications, including simulation experiments and procedures. However, it is expensive and time-consuming to analyze, understand, model and implement the virtual experiments, especially when it is necessary to create new ones from scratch, but also when they must be redesigned and addressed to an audience in a different educational setting. We use UML Activity Diagrams and Petri nets to model experimental procedures and then apply conformance checking to detect possible nonconformities between expected model behavior and actual model execution. As a result, we provide an estimation of the conceptual proximity between experiments performed in different educational settings using the same virtual laboratory software, assisting educators and developers in making informed decisions about software reuse and redesign by providing a systematic and formal way of evaluating software applicability. A virtual microscoping experiment was used as a case study for validation purposes. The results revealed that the specific virtual lab software can be ported, without modifications, from tertiary to secondary education, to achieve learning outcomes relevant to that education level, even though it was originally designed for a distance education university. The proposed framework has potential applications beyond virtual laboratories, as a general approach to process modeling and conformance checking to evaluate the similarity between the specification of experimental procedures and actual execution logs can be applied to various domains.

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“…Although not yet fully explored in the context of cyber-security training analysis, process mining (PM) has great potential to generate comprehensible behavioral models. It has been successful in aiding with similar types of tasks in domains like education [6], cybersecurity [18], healthcare [39], software reliability [17], and several others [11].…”

Section: Process Miningmentioning

confidence: 99%

Applying Process Discovery to Cybersecurity Training: An Experience Report

Macák

Ošlejšek

Bühnová

2022

2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

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Quality improvement of practical cybersecurity training is challenging due to the process-oriented nature of this learning domain. Event logs provide only a sparse preview of trainees' behavior in a form that is difficult to analyze. Process mining has great potential in converting events into behavioral graphs that could provide better cognitive features for understanding users' behavior than the raw data. However, practical usability for learning analytics is affected by many aspects. This paper aims to provide an experience report summarizing key features and obstacles in integrating process discovery into cyber ranges. We describe our lessons learned from applying process mining techniques to data captured in a cyber range, which we have been developing and operating for almost ten years. We discuss lessons learned from the whole workflow that covers data preprocessing, data mapping, and the utilization of process models for the post-training analysis of Capture the Flag games. Tactics addressing scalability are explicitly discussed because scalability has proven to be a challenging task. Interactive data mapping and Capture the Flag specific features are used to address this issue.

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Cybersecurity Analysis via Process Mining: A Systematic Literature Review

Cited by 6 publications

References 59 publications

Towards the Application of Process Mining in the Mining Industry—An LHD Maintenance Process Optimization Case Study

Towards the Application of Process Mining in the Mining Industry—An LHD Maintenance Process Optimization Case Study

Analysis, Evaluation and Reusability of Virtual Laboratory Software Based on Conceptual Modeling and Conformance Checking

Applying Process Discovery to Cybersecurity Training: An Experience Report

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