The Economics of Ransomware-as-a-Service (RaaS) Targeting the Media Supply Chain

Developing Predictive Risk Models

Abstract

The Media and Entertainment (M&E) industry, characterized by high-value digital assets and time-sensitive production cycles, has become a prime target for ransomware-as-a-service (RaaS) operations. This study investigates the economic drivers of RaaS, targeting the media supply chain, and aims to develop predictive models for risk assessment. By analyzing leaked data from RaaS affiliate forums, ransomware variant features, and historical attack data spanning 2019-2024, we identified key organizational characteristics that increase the likelihood of being targeted. These include project phase timing (particularly within 30 days of scheduled release dates), extensive reliance on centralized cloud storage architectures, and mid-market company classifications (100-2,500 employees).

Our comprehensive analysis employed machine learning techniques, including logistic regression, random forest, and gradient boosting models, with the logistic regression model achieving optimal interpretability while maintaining 89% accuracy on the test data. The economic analysis reveals that defensive strategies focusing on immutable backup systems and zero-trust access controls provide the highest return on investment (ROI) by directly disrupting the fundamental economic incentives of the RaaS business model. This study contributes an actionable framework for M&E organizations to prioritize defensive investments and provides policymakers with empirical evidence to shape effective cybercrime deterrence strategies.