Detecting adversarial samples for deep neural networks through mutation testing

• Main Author: Tan, Kye Yen
• Other Authors: Chang Chip Hong
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/138719
• Institution: Nanyang Technological University

Deep Neural Networks (DNNs) are adept at many tasks, with the more well-known task of image recognition using a subset of DNNs called Convolutional Neural Networks (CNNs). However, they are prone to attacks called adversarial attacks. Adversarial attacks are malicious modifications made on input sam...