Artificial Intelligence Technologies in Building Resilient Machine Learning
Guangye Dai, Saurav Sthapit, Gregory Epiphaniou, Carsten R. Maple · IET conference proceedings. · 2021
Since the birth of artificial intelligence, theory and technology are increasingly mature, and the application field is also expanding. Some artificial intelligence technologies, such as deep learning, can help develop resilient machine learning to mitigate adversarial learning attacks. This paper uses a money lending case to explain the application of artificial intelligence in building resilient machine learning, and we use Generative Adversarial Network as an example. Moreover, we discuss the definition of resilient machine learning and give a review of adversarial machine learning attacks and threat actors.