Automated Compliance Blueprint Optimization with Artificial Intelligence

For highly regulated industries such as banking and healthcare, one of the major hindrances to the adoption of cloud computing is compliance with regulatory standards. This is a complex problem due to many regulatory and technical specification (techspec) documents that the companies need to comply with. The critical problem is to establish the mapping between techspecs and regulation controls so that from day one, companies can comply with regulations with minimal effort. We demonstrate the practicality of an approach to automatically analyze regulatory standards using Artificial Intelligence (AI) techniques. We present early results to identify the mapping between techspecs and regulation controls, and discuss challenges that must be overcome for this solution to be fully practical.

Vulnerability Prioritization: An Offensive Security Approach

Organizations struggle to handle sheer number of vulnerabilities in their cloud environments. The de facto methodology used for prioritizing vulnerabilities is to use Common Vulnerability Scoring System (CVSS). However, CVSS has inherent limitations that makes it not ideal for prioritization. In this work, we propose a new way of prioritizing vulnerabilities. Our approach is inspired by how offensive security practitioners perform penetration testing. We evaluate our approach with a real world case study for a large client, and the accuracy of machine learning to automate the process end to end.