Smart Vulnerability Assessment for Scientific Cyberinfrastructure: An Unsupervised Graph Embedding Approach

Steven Ullman, Sagar Samtani, Ben Lazarine, Hongyi Zhu, Benjamin Ampel, Mark Patton, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The accelerated growth of computing technologies has provided interdisciplinary teams a platform for producing innovative research at an unprecedented speed. Advanced scientific cyberinfrastructures, in particular, provide data storage, applications, software, and other resources to facilitate the development of critical scientific discoveries. Users of these environments often rely on custom developed virtual machine (VM) images that are comprised of a diverse array of open source applications. These can include vulnerabilities undetectable by conventional vulnerability scanners. This research aims to identify the installed applications, their vulnerabilities, and how they vary across images in scientific cyberinfrastructure. We propose a novel unsupervised graph embedding framework that captures relationships between applications, as well as vulnerabilities identified on corresponding GitHub repositories. This embedding is used to cluster images with similar applications and vulnerabilities. We evaluate cluster quality using Silhouette, Calinski-Harabasz, and Davies-Bouldin indices, and application vulnerabilities through inspection of selected clusters. Results reveal that images pertaining to genomics research in our research testbed are at greater risk of high-severity shell spawning and data validation vulnerabilities.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE International Conference on Intelligence and Security Informatics, ISI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728188003
DOIs
StatePublished - Nov 9 2020
Event18th IEEE International Conference on Intelligence and Security Informatics, ISI 2020 - Virtual, Arlington, United States
Duration: Nov 9 2020Nov 10 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Intelligence and Security Informatics, ISI 2020

Conference

Conference18th IEEE International Conference on Intelligence and Security Informatics, ISI 2020
Country/TerritoryUnited States
CityVirtual, Arlington
Period11/9/2011/10/20

Keywords

  • GitHub
  • Graph Embedding
  • Scientific cyberinfrastructure
  • virtual machine
  • vulnerability scanning

ASJC Scopus subject areas

  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems

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