Strategic Intelligence Foresight on Ransomware Threats in Indonesian State-Owned Banks

Abstract

The advancement of artificial intelligence (AI) technology in recent years has been aggressively exploited in cyberattacks, particularly through increasingly sophisticated and massive ransomware deployments. Globally, ransomware incidents have risen by 68% over the past two years (Suvorova, 2023), while Indonesia recorded over one million ransomware activities in 2023 alone, with the financial sector being one of the primary targets (BSSN, 2023). State-owned banks (Bank BUMN) are particularly vulnerable due to their classification as critical information infrastructure and their role in managing the nation's strategic financial assets (Crisanto, Prenio, & Restoy, 2023). This study aims to identify the escalation patterns of AI-powered ransomware attacks against state-owned banks in Indonesia, analyze their vulnerability profiles, and formulate early prevention strategies using a strategic intelligence foresight approach for the period 2025–2029. A qualitative method is applied using the scientific inquiry for intelligence analysis framework (Prunckun, 2010) and a five-phase foresight methodology: event identification, trend analysis, driver mapping, scenario development, and policy roadmap formulation (Saritas, 2016). The 2023 LockBit 3.0 ransomware attack on Bank Syariah Indonesia (Chakravarti, 2023) underscores the urgency of integrating foresight into national banking cybersecurity policy formulation.