2020
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan +1
IJCAI 2020poster
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving cars, robotics and financial ser…