Defending AI based FinTech Systems against Model Extraction Attacks

该项目旨在开发新的方法来防御基于人工智能(AI)的金融科技系统免受高效和隐蔽的模型提取攻击，根据攻击，对手可以从系统中窃取AI模型，从而导致知识产权(IP)侵犯、商业优势中断和经济损失。这可以通过检查各种攻击模型、创建主动的和保留实用程序的防御，以及在AI模型上发明不可移除的水印来实现。其成果是部署前保护基于AI的金融科技系统的新工具，以及部署后知识产权侵权取证的工具。这些能力通过提高金融科技系统和其他国家关键人工智能系统的安全性和安全性而受益。

This project aims to develop new methods for defending artificial intelligence (AI) based FinTech systems from highly potent and insidious model extraction attacks whereby an adversary can steal the AI model from the system to cause intellectual property (IP) violation, business advantage disruption, and financial loss. This can be achieved by examining various attack models, creating active and utility-preserving defences, and inventing non-removable watermarks on AI models. The outcomes are new tools for securing AI-based FinTech systems before deployment and tools for IP violation forensics post-deployment. Such capabilities are beneficial by improving the security and safety of FinTech systems and other nationally critical AI systems.