# Cybersecurity in scientific computing: integrity, trust, and security principles in research environments (Lecture 1)

- Institution: CERN
- Speaker: Aleksandra Kowalczuk
- Year: 2026
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3023649)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

The class focuses on cybersecurity as a key element of scientific computing, with particular emphasis on technical integrity, trust, and reproducibility of results in large, distributed research environments such as CERN. It focuses on security principles, architecture, and concepts, showing how a security by design approach supports high quality in modern computing workflows. The principles discussed are cross-domain and applicable to fields that use intensive data pipelines and rely on international collaboration.

The planned session combines a high-level view of system architecture with specific technical mechanisms for protecting code, data, and pipelines. It includes an overview of threats specific to scientific infrastructure, the most common mistakes made by researchers, and practical principles for working securely with e.g. containers, HPC clusters, Grid/Cloud environments, analytical notebooks, and code repositories. Particular emphasis will be placed on data integrity issues, dependency security, architectural aspects of security in complex research projects, and the development of general best practices.

The course is not a general introduction to cybersecurity. It is assumed that participants have basic knowledge, acquired, for example, during previous editions of CERN main or security schools. However, preparatory materials may be made available to ensure that the topic is fully accessible to all participants.

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## Lectures

1. [Cybersecurity in scientific computing: integrity, trust, and security principles in research environments (Lecture 1)](https://invisiblenetwork.ai/learn/cern/3023649/f0ac2ba76738), 1 h 7 min (CERN's player)