Proxima Alpha

Using cyber conflict data from the Dyadic Cyber Incident Dataset (DCID) between China, Russia, Iran, North Korea, and NATO countries (2005–2023), construct a temporal network of cyber aggressions, estimate attack intensity using a Hawkes process, and predict the most likely cyber escalation dyads for 2024.

29-Oct-2025 08:18:07

Step-by-step plan for analysis:

  1. Obtain the Dyadic Cyber Incident Dataset (DCID) data for cyber incidents involving China, Russia, Iran, North Korea, and NATO countries from 2005 to 2023.
  2. Construct a temporal network where nodes represent actors (countries or alliances) and directed edges represent cyber aggression incidents over time.
  3. Use a Hawkes process model to estimate the intensity of attacks, which captures self-exciting behavior typical in cyber conflict data (i.e., attacks provoke subsequent attacks).
  4. Based on the model estimation, predict the most likely dyads for cyber escalation in 2024.
  5. Visualize the temporal network and intensity estimates graphically.

Current status: I am unable to directly access the Dyadic Cyber Incident Dataset (DCID) or exact incident data from 2005-2023 for the specified actors within this session. This dataset is specialized and typically accessed through security research databases or restricted repositories.

To proceed, I require either the dataset file upload from you or a summary of incident counts per dyad per year. Alternatively, I can simulate or outline the Hawkes model method with example synthetic data and produce illustrative visualizations explaining the process clearly.

Please provide the incident data or confirm if I should proceed with a detailed methodological explanation combined with simulated data to fulfill your requirements.