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PubMed Publications| Keyword search (4,163 papers available) |  |
"Dugré M" Authored Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | An analysis of performance bottlenecks in MRI preprocessing | Dugré M; Chatelain Y; Glatard T; | 40072903 ENCS |
| 2 | Predicting Parkinson's disease trajectory using clinical and functional MRI features: A reproduction and replication study | Germani E; Bhagwat N; Dugré M; Gau R; Montillo AA; Nguyen KP; Sokolowski A; Sharp M; Poline JB; Glatard T; | 39982930 ENCS |
| 3 | Longitudinal brain structure changes in Parkinson's disease: A replication study | Sokolowski A; Bhagwat N; Chatelain Y; Dugré M; Hanganu A; Monchi O; McPherson B; Wang M; Poline JB; Sharp M; Glatard T; | 38295031 ENCS |
| 4 | Data and Tools Integration in the Canadian Open Neuroscience Platform | Poline JB; Das S; Glatard T; Madjar C; Dickie EW; Lecours X; Beaudry T; Beck N; Behan B; Brown ST; Bujold D; Beauvais M; Caron B; Czech C; Dharsee M; Dugré M; Evans K; Gee T; Ippoliti G; Kiar G; Knoppers BM; Kuehn T; Le D; Lo D; Mazaheri M; MacFarlane D; Muja N; O' Brien EA; O' Callaghan L; Paiva S; Park P; Quesnel D; Rabelais H; Rioux P; Legault M; Tremblay-Mercier J; Rotenberg D; Stone J; Strauss T; Zaytseva K; Zhou J; Duchesne S; Khan AR; Hill S; Evans AC; | 37024500 ENCS |
| 5 | An analysis of security vulnerabilities in container images for scientific data analysis | Kaur B; Dugré M; Hanna A; Glatard T; | 34080631 ENCS |
| Title: | An analysis of security vulnerabilities in container images for scientific data analysis | ||||
| Authors: | Kaur B, Dugré M, Hanna A, Glatard T | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/34080631/ | ||||
| DOI: | 10.1093/gigascience/giab025 | ||||
| Publication: | GigaScience | ||||
| Keywords: | Docker; containers; neuroimaging; security vulnerabilities; singularity; | ||||
| PMID: | 34080631 | Category: | Date Added: | 2021-06-03 | |
| Dept Affiliation: |
ENCS
1 Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 1M8, Canada. |
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Description: |
Background: Software containers greatly facilitate the deployment and reproducibility of scientific data analyses in various platforms. However, container images often contain outdated or unnecessary software packages, which increases the number of security vulnerabilities in the images, widens the attack surface in the container host, and creates substantial security risks for computing infrastructures at large. This article presents a vulnerability analysis of container images for scientific data analysis. We compare results obtained with 4 vulnerability scanners, focusing on the use case of neuroscience data analysis, and quantifying the effect of image update and minification on the number of vulnerabilities. Results: We find that container images used for neuroscience data analysis contain hundreds of vulnerabilities, that software updates remove roughly two-thirds of these vulnerabilities, and that removing unused packages is also effective. Conclusions: We provide recommendations on how to build container images with fewer vulnerabilities. |
