Internet Outages During Times of Conflict

We analyze datasets collected by the Center for Applied Internet Data Analysis (CAIDA) and the Réseaux IP Europeéns (RIPE) sites to demonstrate the efficacy of machine learning models in predicting Internet outages and disruptions that affect and hinder network access to essential services and humanitarian aid in times of conflict. Custom datasets for specific geographic areas are created using data filtering. A sliding time window transformation was applied to design models that accurately predict disruptions. Model performance is evaluated based on the prediction accuracy using Internet Outage Detection and Analysis (IODA) and RIPE datasets.