Digital Cyber Twins are sophisticated virtual representations of physical assets, systems, and processes that are constructed through the use of data. These digital replicas differ from virtualized IT such as containers, which are purely technological solutions, in that they offer a comprehensive understanding of an organization's attack surface and threat landscape, essential for effective and efficient continuous cyber threat susceptibility analysis and continuous risk assessment.
The integration of different types, formats, and sources of security information, necessary to construct the digital cyber twin, is facilitated through traditional Knowledge Representation & Reasoning techniques. These techniques provide a more accurate and comprehensive representation of the threat landscape, allowing for effective and informed decision-making. The digital cyber twin serves as a unified representation of an organization's security posture, making it easier to identify and prioritize areas of risk and to continuously monitor and assess the threat landscape.
Data collection from the attack surface and threat landscape can be performed continuously, enabling organizations to stay ahead of emerging threats and respond to changes in their environment in real-time. This continuous monitoring and assessment, facilitated by the digital cyber twin, enables early detection and response to cyber attacks, mitigating their impact and reducing the risk of significant damage.
Conversely, red teaming and pentesting, while useful for assessing an organization's security posture, have limitations when used for cyber threat susceptibility analysis. These methods provide snapshots in time and are often not inclusive of all operational IT assets necessary for a holistic assessment. They also typically focus on simulating known attack scenarios rather than continuously monitoring and assessing the threat landscape.
In summary, Digital Cyber Twins are a valuable tool for organizations seeking to continuously monitor and assess their susceptibility to cyber threats. The integration of different types, formats, and sources of security information, facilitated through traditional Knowledge Representation & Reasoning techniques, results in a comprehensive and accurate representation of the threat landscape, supporting informed decision-making and continuous risk assessment. The continuous data collection from the attack surface and threat landscape enables organizations to stay ahead of emerging threats and respond to changes in their environment in real-time, mitigating the impact of cyber attacks and reducing the risk of significant damage.