Artificial Intelligence has made a significant contribution to autonomous vehicles, from object detection to path planning. However, AI models require a large amount of sensitive training data and are usually computationally intensive to build. The commercial value of such models motivates attackers to mount various attacks. Adversaries can launch model extraction attacks for monetization purposes or step-ping-stone towards other attacks like model evasion. In specific cases, it even results in destroying brand reputation, differentiation, and value proposition. In addition, IP laws and AI-related legalities are still evolving and are not uniform across countries. We discuss model extraction attacks in detail with two use-cases and a generic kill-chain that can compromise autonomous cars. It is essential to investigate strategies to manage and mitigate the risk of model theft.
翻译:人工智能对自主车辆作出了重大贡献,从物体探测到路径规划,但人工智能模型需要大量敏感培训数据,通常在计算上密集建立。这些模型的商业价值促使袭击者发动各种袭击。反政府分子可以以货币化为目的发动模型抽取攻击,或向其他攻击(如逃生模型)划入一步。在特定情况下,甚至导致破坏品牌声誉、差异和价值主张。此外,知识产权法和与AI有关的法律仍在发展,而且各国并不统一。我们详细讨论模型抽取攻击,同时使用两个使用案例和一个可能损害自主汽车的通用杀手链。必须调查管理和降低模式盗窃风险的战略。