Securing Artificial Intelligence: Exploring Attack Scenarios and Defense Strategies

In today's landscape, the widespread integration of artificial intelligence (AI) solutions across diverse domains has become commonplace. Yet, despite its omnipresence, AI applications, often lack adequate protection, leaving them vulnerable to various threats. Consequently, businesses find themselves in need of clear guidance to navigate these risks effectively. This study aims to address this gap by shedding light on attacker activities targeting AI applications, offering robust defense mechanisms, and creating a comprehensive checklist for evaluating current processes. By analyzing attack and defense strategies, it is clear that although these methods are similar to those used in traditional information systems, their implementation in AI contexts differs significantly. This study provides detailed implementation insights and a security checklist to help organizations assess process maturity quickly. By identifying and addressing security gaps promptly, organizations can enhance the resilience of their AI infrastructure.