Differential training: A generic framework to reduce label noises for Android malware detection

• Main Authors: XU, Jiayun, LI, Yingjiu, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Databases and Information Systems; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/6551; https://ink.library.smu.edu.sg/context/sis_research/article/7554/viewcontent/Differential_training_A_generic_framework_to_reduce_label_noises_for_Android_malware_detection.pdf
• Institution: Singapore Management University

A common problem in machine learning-based malware detection is that training data may contain noisy labels and it is challenging to make the training data noise-free at a large scale. To address this problem, we propose a generic framework to reduce the noise level of training data for the training...