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Understanding Information Asymmetry in Securing AI Systems
This chapter explores the concept of information asymmetry between attackers and defenders in securing AI systems. It discusses the onus on defenders to fortify their systems, the limitations of security by obscurity, and the exploitation of machine learning models. The chapter highlights the importance of transparency, collaboration, and common defense in effectively securing machine learning systems.