The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Security in DevSecOps: Applying Tools and Machine Learning to Verification and Monitoring Steps
Open accessAbstract
Security represents one of the crucial concerns when it comes to DevOps methodology-empowered software development and service delivery process. Considering the adoption of Infrastructure as Code (IaC), even minor flaws could potentially cause fatal consequences, especially in sensitive domains such as healthcare and maritime applications. However, most of the existing solutions tackle either Static Application Security Testing (SAST) or run-time behavior analysis distinctly. In this paper, we propose a) IaC Scan Runner, an open-source solution developed in Python for inspecting a variety of state-of-the-art IaC languages in application design time and b) the run time anomaly detection tool called LOMOS. Both tools work in synergy and provide a valuable contribution to a DevSecOps tool set. The proposed approach is demonstrated and their results will be demonstrated on various case studies showcasing the capabilities of static analysis tool IaC Scan Runner combined with LOMOS - log analysis artificial intelligence-enabled framework.
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Highly regulated sectors such as healthcare, finance, and government face additional hurdles due to stringent compliance requirements, further complicating DevSecOps implementation.
“Highly regulated sectors such as healthcare, finance, and government face additional hurdles due to stringent compliance requirements, further complicating DevSecOps implementation.”
From Evolution of DevSecOps and Its Influence on Application Security: A Systematic Literature Review (2025) · cites this paper as [17]
Section 5 (page unavailable) describes checking application compliance with standards as a complex task for auditors, and the Abstract identifies healthcare as a sensitive domain. The paper does not say that stringent compliance requirements create additional DevSecOps implementation hurdles in healthcare, finance, and government. (LLM, conf=0.76)
Experimental — accuracy not yet measuredOrganisations often encounter resistance to change, skill shortages, and the technical complexity of integrating security tools into CI/CD pipelines.
“Organisations often encounter resistance to change, skill shortages, and the technical complexity of integrating security tools into Continuous Integration/Continuous Deployment (CI/CD) pipelines.”
From Evolution of DevSecOps and Its Influence on Application Security: A Systematic Literature Review (2025) · cites this paper as [17]
The Introduction and §2.1 describe DevSecOps workflows, and §3 describes a service that integrates security-scanning tools. None says organisations often face resistance to change, skill shortages, or technical complexity as a barrier to integrating those tools into CI/CD pipelines. Searches for those barriers and for DevSecOps adoption challenges found no supporting passage in our copy. (LLM, conf=0.73)
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Citations
Cites
LogBERT: Log Anomaly Detection via BERT
Guo, H., Yuan, S., & Wu, X. (2021) · 2021 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn52387.2021.9534113 · Cited by 454
Detecting code smells using machine learning techniques: Are we there yet?
Nucci, D. D., Palomba, F., Tamburri, D. A., Serebrenik, A., & Lucia, A. D. (2018) · IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · doi:10.1109/saner.2018.8330266 · Cited by 304
Unsupervised log message anomaly detection
Farzad, A., & Gulliver, T. A. (2020) · ICT Express · doi:10.1016/j.icte.2020.06.003 · Cited by 135
BERT-Log: Anomaly Detection for System Logs Based on Pre-trained Language Model
Chen, S., & Liao, H. (2022) · Applied Artificial Intelligence · doi:10.1080/08839514.2022.2145642 · Cited by 107
Embracing IaC Through the DevSecOps Philosophy: Concepts, Challenges, and a Reference Framework
Alonso, J., Piliszek, R., & Cankar, M. (2023) · IEEE Software · doi:10.1109/ms.2022.3212194 · Cited by 30
Self-citationAutomated Approach to IaC Code Inspection Using Python-Based DevSecOps Tool
Petrović, N., Cankar, M., & Luzar, A. (2022) · Telecommunications Forum (TELFOR) · doi:10.1109/telfor56187.2022.9983681 · Cited by 15
Self-citationLogBERT: Log Anomaly Detection via BERTPreprint
Guo, H., Yuan, S., & Wu, X. (2021) · arXiv (Cornell University) · doi:10.26076/0567-4901 · Cited by 7
Log analysis and system monitoring with nfer
Kauffman, S. (2022) · Science of Computer Programming · doi:10.1016/j.scico.2022.102909 · Cited by 7
LogBERT: Log Anomaly Detection via BERT
Guo, H., Yuan, S., & Wu, X. (2021) · arXiv · doi:10.48550/arxiv.2103.04475 · Cited by 7
Automatic log analysis with NLP for the CMS workflow handling
Layer, L., Abercrombie, D. R., Bakhshiansohi, H., et al. (2020) · EPJ Web of Conferences · doi:10.1051/epjconf/202024503006 · Cited by 6
Web Log Analysis and Security Assessment Method Based on Data Mining
Jin, J., & Lin, X. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/8485014 · Cited by 2
Flagged first, then by citations
Research works printed but not linked: 5
- Juncal Alonso, Christophe Joubert, Leire Orue-Echevarria, Matteo Pradella, and Daniel Vladu?ic. 2021. Programming trustworthy Infrastructure As Code in a Secure Framework. In First SWForum workshop on Trustworthy Software and Open Source 2021. 1--8.
- Kerim Goztepe. 2012. Designing Fuzzy Rule Based Expert System for Cyber Security. International Journal of Information Security Science 1 (01 2012), 13--19.
- 10.1155/2022 · DOI
- 10.1051/epjconf · DOI
- Jina Kim Yukyung Lee and Pilsung Kang. 2021. LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model. arXiv preprint 211109564 (2021).
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Artificial Intelligence in Maritime Anomaly Detection: A Decadal Bibliometric Analysis (2014–2024)
Thakur, A. S., Alex, T. L., & Nighojkar, A. (2025) · Journal of The Institution of Engineers (India) Series C · doi:10.1007/s40032-025-01169-w · Cited by 14
Vulnerabilities in infrastructure as code: what, how many, and who?
War, A., Diallo, A., Habib, A., Klein, J., & Bissyandé, T. F. (2025) · Empirical Software Engineering · doi:10.1007/s10664-025-10672-8 · Cited by 11
Binbeshr, F., & Imam, M. M. (2025) · International Conference on Evaluation and Assessment in Software Engineering (EASE) · doi:10.1145/3727967.3756841 · Cited by 8
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Nagasundari, S., Manja, P., Mathur, P., & Honnavalli, P. B. (2025) · IEEE Access · doi:10.1109/access.2025.3547932 · Cited by 12
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Mohammed, K., Shanmugam, B., & El-Den, J. (2025) · Technologies · doi:10.3390/technologies13120548 · Cited by 8
Security Vulnerabilities in Infrastructure as Code: What, How Many, and Who?Preprint
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AI-BASED FRAUD DECTECTION SYSTEM
-, S. N. (2025) · International Journal on Science and Technology · doi:10.71097/ijsat.v16.i2.6435
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Pasic, A., & González-Zarzosa, S. (2026) · Springer eBooks · doi:10.1007/978-3-032-25917-2_1
Metadata
- Authors
- Cankar, M., Petrovic, N., Pita Costa, J., Cernivec, A., Antic, J., Martincic, T., & Stepec, D.
- Affiliations
- XLAB (Slovenia) (SI)
- XLAB d.o.o. & University of Nis, Ljubljana, Slovenia
- XLAB d.o.o., Ljubljana, Slovenia
- ORCID
- Venue
- Companion of the 2023 ACM/SPEC International Conference on Performance Engineering
- Publisher
- ACM
- Published
- 2023-04-15
- Pages
- 201-205
- OpenAlex
- W4362489974
- Cited by
- 24
- References
- 8
- Citations by year
- 2026: 3 · 2025: 12 · 2024: 3 · 2023: 6
- FWCI
- 7.25
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- ACM/SPEC International Conference on Performance Engineering (ICPE) (publishedVersion, cc-by)
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Funders
- HORIZON EUROPE Framework Programme (101070177, 101073821, 101095542)
- Horizon 2020 Framework Programme (101000162,952644,952633)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Information Systems › Web Application Security Vulnerabilities
- Keywords
- DevSecOps, infrastructure as code, static analysis, log analysis, machine learning, security verification, security monitoring, open source tools
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