Visible to the public CVSS-based Vulnerability and Risk Assessment for High Performance Computing Networks

TitleCVSS-based Vulnerability and Risk Assessment for High Performance Computing Networks
Publication TypeConference Paper
Year of Publication2022
AuthorsDebnath, Jayanta K., Xie, Derock
Conference Name2022 IEEE International Systems Conference (SysCon)
Keywordsattack graph, CVSS, HPC, Knowledge engineering, Network security, Numerical models, pubcrawl, Real-time Systems, Resiliency, risk assessment, Scalability, standardization, Stochastic Computing Security, Stochastic processes, Throughput, Vulnerability
AbstractCommon Vulnerability Scoring System (CVSS) is intended to capture the key characteristics of a vulnerability and correspondingly produce a numerical score to indicate the severity. Important efforts are conducted for building a CVSS stochastic model in order to provide a high-level risk assessment to better support cybersecurity decision-making. However, these efforts consider nothing regarding HPC (High-Performance Computing) networks using a Science Demilitary Zone (DMZ) architecture that has special design principles to facilitate data transition, analysis, and store through in a broadband backbone. In this paper, an HPCvul (CVSS-based vulnerability and risk assessment) approach is proposed for HPC networks in order to provide an understanding of the ongoing awareness of the HPC security situation under a dynamic cybersecurity environment. For such a purpose, HPCvul advocates the standardization of the collected security-related data from the network to achieve data portability. HPCvul adopts an attack graph to model the likelihood of successful exploitation of a vulnerability. It is able to merge multiple attack graphs from different HPC subnets to yield a full picture of a large HPC network. Substantial results are presented in this work to demonstrate HPCvul design and its performance.
DOI10.1109/SysCon53536.2022.9773931
Citation Keydebnath_cvss-based_2022