Security in DevSecOps: Applying Tools and Machine Learning to Verification and Monitoring Steps-Reference-Cited by-同舟云学术

Security in DevSecOps: Applying Tools and Machine Learning to Verification and Monitoring Steps

Published:2023-04-15 Issue: Volume: Page:
ISSN:
Container-title:Companion of the 2023 ACM/SPEC International Conference on Performance Engineering
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Author:

Cankar Matija¹^ORCID,Petrovic Nenad²^ORCID,Pita Costa Joao¹^ORCID,Cernivec Ales¹^ORCID,Antic Jan¹^ORCID,Martincic Tomaz¹^ORCID,Stepec Dejan¹^ORCID

Affiliation:

1. XLAB d.o.o., Ljubljana, Slovenia

2. XLAB d.o.o. & University of Nis, Ljubljana, Slovenia

Funder

HORIZON EUROPE Framework Programme

Horizon 2020 Framework Programme

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3578245.3584943

Reference14 articles.

1. 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. 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.

2. Embracing IaC Through the DevSecOps Philosophy: Concepts, Challenges, and a Reference Framework

3. BERT-Log: Anomaly Detection for System Logs Based on Pre-trained Language Model

4. Detecting code smells using machine learning techniques: Are we there yet?

5. Unsupervised log message anomaly detection

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