Towards Developing a Scalable Cyber Risk Assessment and Mitigation Framework

The increasing dependence on digital technology and the internet has made cybersecurity a critical issue for organizations, with cyber-attacks becoming more frequent and sophisticated. In this context, cyber risk evaluation and mitigation have become essential components of modern cyber infrastructures to ensure the security and resilience of digital assets and services in the face of ever-evolving cyber threats. This paper aims to emphasize the significance of the Cyberthreats and Vulnerability Information Analysis to proactively understand the cyber risks and abnormalities in real-time and provide appropriate mitigation strategies. Our work incorporates an inferencing layer to our AI-engine focusing on cyber risk assessment and mitigation. This inferencing layer prioritizes significant risks and presents a mitigation plan to address them. We discuss the key steps and processes implemented as part of the cyber risk and mitigation (CRAM) framework including use of machine learning algorithms for risk assessment and mitigation. Furthermore, we evaluate and compare the effectiveness of the mitigation plan using strategies provided by the MITRE Corporation, a trusted source in cybersecurity. Overall, this paper highlights the importance of incorporating a real-time risk assessment and mitigation system in organizations' cybersecurity infrastructure. Our proposed framework provides a practical and efficient solution to identify and address potential cyber threats, minimizing the risk of data breaches and financial loss.