A Statistical Defense Approach for Detecting Adversarial Examples

• Published in: arXiv.org
• Main Authors: Cennamo, Alessandro, Freeman, Ido, Kummert, Anton
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 26.08.2019
• Subjects: Neural networks; Statistical analysis; Statistical methods

Adversarial examples are maliciously modified inputs created to fool deep neural networks (DNN). The discovery of such inputs presents a major issue to the expansion of DNN-based solutions. Many researchers have already contributed to the topic, providing both cutting edge-attack techniques and vari...