How to Use AI for Decision Making for Vulnerability Remediation Planning

As organizations continue to adapt many security and risk management platforms into their security posture, potential gaps in their security may emerge. We live in a data-centric world, with Artificial Intelligence (AI) as the engine that increasingly drives decision-making. Cybersecurity and industries all seek to make smarter and more reliable decisions with minimum cost, often working with a complete picture, to gain competitive advantages. Cybersecurity is looking for smarter remediation decisions, based on current circumstances, to use the maximum benefits of security tools and resources.
In this presentation we’ll focus on one domain, vulnerability remediation, and how to use the Artificial Intelligence (AI) Deep Machine Learning (DML) to provide each client with the best remediation plan based on many criteria including but not limited to Risk, Assets, Infrastructure, Threat Intel, Client’s size and more.
We will provide the main concept of how we can use AI in remediation planning and let the system decide What, When, and How (WWH) the remediation could be done including patching, configuration, and predicated risks.