DeepHunter: A coverage-guided fuzz testing framework for deep neural networks

• Main Authors: XIE, Xiaofei, MA, Lei, JUEFEI-XU, Felix, XUE, Minhui, CHEN, Hongxu, LIU, Yang, ZHAO, Jianjun, LI, Bo, YIN, Jianxiong, SEE, Simon
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: OS and Networks; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/7064; https://ink.library.smu.edu.sg/context/sis_research/article/8067/viewcontent/3293882.3330579.pdf
• Institution: Singapore Management University

The past decade has seen the great potential of applying deep neural network (DNN) based software to safety-critical scenarios, such as autonomous driving. Similar to traditional software, DNNs could exhibit incorrect behaviors, caused by hidden defects, leading to severe accidents and losses. In th...