Cyber Threat Modeling: Enhancing Digital Cyber Twin's Cyber Threat Susceptibility Assessment

As the digital world continues to expand, organizations are facing an increasing number of cyber threats. To effectively manage and mitigate these threats, a continuous threat exposure management program is essential. The Digital Cyber Twin can be used to perform cyber threat susceptibility assessments on the organization's IT enterprise. In this article, we will explore the ten key aspects of cyber threat modeling and how they support the Digital Cyber Twin in performing a better cyber threat susceptibility assessment of the organization.

1. Intent: Understanding the intent of an attacker is critical in cyber threat modeling. The Digital Cyber Twin can use this information to identify the types of attacks that may be carried out and the potential impact they could have on the organization. This allows the Digital Cyber Twin to develop targeted threat mitigation strategies.
2. Capability: Understanding the overall capability of the adversary is important in prioritizing mitigation efforts. The Digital Cyber Twin can use this information to determine which attacks are most likely to be successful and which security measures should be implemented to mitigate these attacks.
3. Opportunity: The Digital Cyber Twin can identify the conditions and factors that make the organization vulnerable to attack. By understanding the opportunities available to an attacker, the Digital Cyber Twin can develop strategies to mitigate these vulnerabilities.
4. TTPs: Understanding the tactics, techniques, and procedures (TTPs) used by attackers can help the Digital Cyber Twin to better understand the methods used by attackers and develop effective countermeasures.
5. Victim Industry: Understanding the industry or sector targeted by the adversary is essential in developing effective mitigation strategies. Different industries have different vulnerabilities and attack surfaces, and the Digital Cyber Twin can use this information to develop targeted security measures.
6. Victim Location: The geographic location of the victim organization can help to identify potential threats and vulnerabilities. The Digital Cyber Twin can use this information to develop strategies to mitigate the risks associated with specific locations.
7. Adversary Location: Understanding the location of the threat actor can help the Digital Cyber Twin to prepare for potential threats. Adversaries located in certain regions may be more likely to carry out certain types of attacks, and the Digital Cyber Twin can use this information to implement targeted security measures.
8. Historical Activity: Analyzing the historical activity of an adversary is important in identifying patterns and trends in their behavior. This information can be used to develop effective mitigation strategies and prepare for potential future attacks.
9. Emerging Threats: The threat landscape is constantly evolving, and identifying emerging threats is critical to effective cyber threat modeling. The Digital Cyber Twin must stay up-to-date with the latest threats and vulnerabilities to develop effective mitigation strategies.
10. Mitigation Strategies: Finally, the Digital Cyber Twin must develop effective mitigation strategies to reduce the risk of an attack. This involves identifying potential threats and vulnerabilities and implementing controls to mitigate these risks.

In the context of the 10 key aspects from threat modeling, the transparency and explainability features of a machine reasoning-based digital cyber twin are particularly important. By leveraging knowledge representation and reasoning (KRR) technologies, a digital cyber twin can more effectively reason about and analyze the various threat modeling inputs such as intent, capability, TTPs, historical activity, emerging threats, and mitigation strategies. The transparency and explainability of KRR-based approaches enable cybersecurity professionals to better understand and interpret the results of the digital cyber twin's analysis, which in turn allows for more effective decision-making and threat response. Additionally, the ability to trace and explain the reasoning behind the digital cyber twin's outputs can provide valuable insights into the threat landscape, helping organizations stay ahead of evolving threats and vulnerabilities.

In conclusion, cyber threat modeling is essential in supporting the Digital Cyber Twin to perform a better cyber threat susceptibility assessment of the organization. Understanding the intent, capability, opportunity, TTPs, victim industry, victim location, adversary location, historical activity, emerging threats, and mitigation strategies is critical to developing effective countermeasures and reducing the overall risk of a cyber attack. By leveraging the information from cyber threat modeling, the Digital Cyber Twin can help organizations to be better prepared and more resilient against cyber threats with full transparency and explainability.