Abstract
Cloud platform providers offer security tools that their customers can use to scan their cloud systems for vulnerabilities. Such scans are carried out with a predetermined series of steps and algorithms because of a lack of a scalable, data-driven mechanism to customize the scanning process. This disclosure describes techniques to customize the scanning approach by leveraging historical scan results to derive insight from relationships between information logged from different scans. Per the techniques, a matrix of correlations between different categories of vulnerabilities is generated based on the historical data. The insight derived from the correlation matrix is employed to adjust the scanning operation by supporting partial scanning with predictive results, detecting and highlighting vulnerabilities that are already resolved, and recommending security product tiers with capabilities suited for a customer’s specific needs. The customization can be based on attributes such as customer industry, region, product, operating environment, etc. By prioritizing earlier detection of the more critical vulnerabilities and checking whether vulnerabilities have already been rectified, the techniques can make scanning faster and more efficient
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Bhatnagar, Yash and Singh, Saumya, "Custom Vulnerability Scans on Cloud Platforms Based on Historical Data", Technical Disclosure Commons, (January 20, 2025)
https://www.tdcommons.org/dpubs_series/7745