ATM: Automated Threat Modelling for Enterprise AI-enabled Assets

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In today's AI and Digital era, most companies work with, deploy, or are using AI assets incorporating machine learning/deep learning models. In this context, AI assists enterprises in their decision-making process. However, AI-enabled asset manufacturers mainly focus on designing, training and deploying AI-based solutions without considering security requirements. As a result, AI-based attacks have become common over recent years. These attacks can potentially manipulate the decision-making of AI-enabled assets in a way that would be imperceptible to humans. The most common attacks on AI/ML Modelling, Data Poisoning and Transfer Learning Attacks.Although autonomous AI-assisted threat modelling can facilitate not only the design of a comprehensive and accurate threat model but also assist with making an appropriate response. To the best of our knowledge, there is no autonomous AI-enabled threat-modelling solution to analyse threats against AI-enabled assets in great depth. Moreover, existing vulnerability assessment approaches do not ensure the confidentiality of clients' data.In this regard, we propose to develop an AI-assisted Automated Threat Modelling(ATM) System that will help detect all the threats related to the AI-enabled asset by generating a Threat Model, providing countermeasures, and prioritising them to mitigate discovered threats.